ʻO Abderahman Rejeb a , Alireza Abdollahi b , Karim Rejeb c , Horst Treiblmaier d,
- a Keʻena o ka hoʻokele a me ke kānāwai, Faculty of Economics, University of Rome Tor Vergata, Via Columbia, 2, Roma 00133, Italia
- b Keʻena o ka ʻoihana ʻoihana, ke kumu o ka hoʻokele, ke Kulanui ʻo Kharazmi, 1599964511 Tehran, Iran
- c Kumu ʻepekema o Bizerte, Kulanui o Carthage, Zarzouna, 7021 Bizerte, Tunisia
- d Kula o International Management, Modul University Vienna, Am Kahlenberg 1, 1190 Vienna, Austria
OLELO HOOLAHA | KANAWAI |
Keywords: Drones UAV ʻO ka mahiʻai kūpono Internet o Mau Paipalapalapala | ʻO Drones, i kapa ʻia ʻo Unmanned Aerial Vehicles (UAV), ua ʻike i kahi hoʻomohala kupaianaha i nā makahiki i hala iho nei. Ma ka mahiʻai, ua hoʻololi lākou i nā hana mahiʻai ma o ka hāʻawi ʻana i ka poʻe mahiʻai i ka mālama kālā nui, hoʻonui ʻoi aku ka maikaʻi o ka hana, a ʻoi aku ka maikaʻi. I nā makahiki i hala iho nei, aia ke kumuhana o nā drones mahiʻai ua hoʻokipa maikaʻi ʻia ka manaʻo hoʻonaʻauao. No laila, hana mākou i kahi loiloi piha e pili ana i ka bibliometrics e hōʻuluʻulu a hoʻonohonoho i nā palapala hoʻonaʻauao e kū nei a hōʻike i nā ʻano noiʻi o kēia manawa a me nā wahi wela. mākou e hoʻohana i nā ʻenehana bibliometric a e kālailai i nā palapala e pili ana i nā drones mahiʻai e hōʻuluʻulu a e loiloi i ka noiʻi mua. Hōʻike kā mākou loiloi i ka ʻike mamao, ka mahiʻai pololei, ke aʻo hohonu, ke aʻo ʻana i ka mīkini, a me ka Pūnaewele o nā Mea he mau kumuhana koʻikoʻi e pili ana i nā drones mahiʻai. ʻO ka hui pū ʻana hōʻike ʻia ka nānā ʻana i ʻeono mau pūʻulu noiʻi ākea ma ka palapala. ʻO kēia haʻawina kekahi o nā hoʻāʻo mua e hōʻuluʻulu i ka noiʻi drone i ka mahiʻai a hōʻike i nā kuhikuhi noiʻi e hiki mai ana. |
Introduction
ʻO ka mahiʻai ke kumu meaʻai mua o ka honua (Friha et al., 2021), a ke kū nei i nā pilikia koʻikoʻi ma muli o ka
ka hoʻonui ʻana i ka noi no nā huahana meaʻai, ka palekana o ka meaʻai, a me nā hopohopo palekana e like me ke kāhea ʻana i ka mālama ʻana i ke kaiapuni, mālama wai, a
hoʻomau (Inoue, 2020). Manaʻo ʻia kēia hoʻomohala ʻana e hoʻomau ʻia mai ka manaʻo o ka heluna kanaka o ka honua e hiki i 9.7 biliona e 2050
(2019). No ka mea ʻo ka mahiʻai ka laʻana koʻikoʻi o ka hoʻohana ʻana i ka wai ma ka honua holoʻokoʻa, ua manaʻo ʻia e koi ʻia ka meaʻai a me ka wai.
e hoʻonui nui ʻia ka hoʻohana ʻana i ka wā e hiki mai ana. Eia kekahi, ʻo ka hoʻonui ʻana i ka hoʻohana ʻana i nā mea kanu a me nā pesticides
i hui pū ʻia me ka hoʻoikaika ʻana i nā hana mahiʻai hiki ke alakaʻi i nā pilikia kaiapuni e hiki mai ana. Pēlā nō, palena ʻia ka ʻāina mahiʻai, a me ka
ke emi nei ka nui o ka poe mahiai a puni ka honua. ʻO kēia mau pilikia e hoʻokūpaʻa i ka pono o nā ʻōnaehana mahiʻai hou a hoʻomau (Elijah
et al., 2018; Friha et al., 2021; Inoue, 2020; Tzounis et al., 2017).
ʻO ka hoʻokomo ʻana i nā ʻenehana hou i ʻike ʻia he hopena hoʻohiki e hoʻoponopono ai i kēia mau pilikia. ʻO ka mahiʻai akamai (Brewster et al.,
2017; ʻO Tang et al., 2021) a me ka mahiʻai pololei (Feng et al., 2019; Khanna & Kaur, 2019) i puka mai ma muli o ia mau hoʻopaʻapaʻa. ʻO ka
ʻO ka mua he manaʻo maʻamau no ka hoʻohana ʻana i nā ʻenehana kamaʻilio ʻike (ICT) a me nā mea hou hou i ka hana mahiʻai e hoʻonui ai i ka pono a me ka pono (Haque et al., 2021). ʻO ka mea hope e kālele ana i ka hoʻokele kahua kikoʻī kahi i māhele ʻia ai ka ʻāina
ʻāpana homogeneous, a loaʻa i kēlā me kēia ʻāpana ka nui o ka hoʻokomo ʻana i ka mahiʻai no ka hoʻonui ʻana i ka huaʻai ma o nā ʻenehana hou (Feng et al., 2019; Khanna & Kaur, 2019). ʻO nā ʻenehana koʻikoʻi i hoʻowalewale i ka manaʻo o ka poʻe ʻepekema ma kēia kahua ʻo Wireless Sensor Networks (WSNs) (J. Zheng & Yang, 2018; Y. Zhou et al., 2016), ka Internet of Things (IoT) (Gill et al., 2017; He et al., 2021; Liu et al., 2019),
nā ʻenehana naʻauao (AI), me ka aʻo ʻana i ka mīkini a me ke aʻo hohonu (Liakos et al., 2018; Parsaeian et al., 2020; Shadrin et al.,
2019), nā ʻenehana helu (Hsu et al., 2020; Jinbo et al., 2019; Zamora-Izquierdo et al., 2019), ʻikepili nui (Gill et al., 2017; Tantalaki
et al., 2019), a me blockchain (PW Khan et al., 2020; Pincheira et al., 2021).
Ma waho aʻe o nā ʻenehana i ʻōlelo ʻia ma luna, ua manaʻo ʻia ka ʻike mamao he mea hana ʻenehana me ka hiki ke hoʻomaikaʻi.
mahiʻai akamai a pololei. ʻO nā Satellites, nā mokulele i hana ʻia e ke kanaka, a me nā drones he mau ʻenehana mamao-sensing kaulana (Tsouros et al., 2019).
ʻO nā Drones, i ʻike nui ʻia ʻo Unmanned Aerial Vehicles (UAVs), Unmanned Aircraft Systems (UAS), a me nā mokulele i hoʻokele mamao ʻia.
koʻikoʻi koʻikoʻi no ka mea he nui nā pono i hoʻohālikelike ʻia me nā ʻenehana mamao-sensing ʻē aʻe. No ka laʻana, hiki i nā drones ke hāʻawi
nā kiʻi kiʻekiʻe a me nā kiʻi hoʻonā kiʻekiʻe i nā lā ao (Manfreda et al., 2018). Eia kekahi, ʻo kā lākou loaʻa a me ka wikiwiki o ka hoʻololi ʻana he mea ʻē aʻe
pono (Radoglou-Grammatikis et al., 2020). Ke hoʻohālikelike ʻia me nā mokulele, ʻoi aku ka maikaʻi o nā drones a maʻalahi hoʻi e hoʻonohonoho a mālama (Tsouros et al., 2019). ʻOiai ua hoʻohana mua ʻia no ka hana kaua, hiki i nā drones ke hoʻopōmaikaʻi i nā noi kīwila he nui, no ka laʻana i ka hoʻokele chain chain (A. Rejeb, Rejeb, et al., 2021a), no nā kumu kōkua kanaka (A. Rejeb, Rejeb, et al., 2021c), ka mahiʻai akamai, ka nānā ʻana a me ka palapala ʻāina, nā palapala hoʻoilina moʻomeheu, ka hoʻokele pōʻino, a me ka mālama nahele a me nā holoholona hihiu (Panday, Pratihast, et al., 2020). Ma ka mahiʻai, nui nā wahi noi o nā drones i hiki ke hoʻohui ʻia me nā ʻenehana hou, nā mana helu, a me nā mea ʻike ma luna o ka papa e kākoʻo i ka hoʻokele ʻana i nā mea kanu (e laʻa, ka palapala ʻāina, ka nānā ʻana, ka irrigation, ka ʻike mea kanu) (H. Huang et al., 2021) , hōʻemi pōʻino, ʻōnaehana hoʻolaha mua, mālama holoholona hihiu a me nā ululāʻau e inoa i kekahi (Negash et al., 2019). Pēlā nō, hiki ke hoʻohana ʻia nā drones i kekahi mau hana mahiʻai, me ka nānā ʻana i ka huaʻai a me ka ulu ʻana, ka manaʻo o ka hua, ka loiloi wai, a me ka mauʻu, nā pest, a me ka ʻike maʻi (Inoue, 2020; Panday, Pratihast, et al., 2020). ʻAʻole hiki ke hoʻohana wale ʻia nā drones no ka nānā ʻana, ka helu ʻana, a me nā kumu ʻike e pili ana i kā lākou ʻikepili sensory, akā no ka irrigation pololei a me ka weed precision, pest, a me ka hoʻokele maʻi. I nā huaʻōlelo ʻē aʻe, hiki i nā drones ke pīpī i ka wai a me nā pesticides i nā helu kikoʻī e pili ana i ka ʻikepili kaiapuni. Ua hōʻuluʻulu ʻia nā pōmaikaʻi o nā drones i ka mahiʻai ma ka Papa 1.
ʻO nā pōmaikaʻi nui o nā drones i ka mahiʻai.
pono | Kuhikuhi(s) |
Hoʻonui i ke kino a me ke kiko ʻike i nā ʻōlelo hoʻoholo | (Gago et al., 2015; Niu et al., 2020; Srivastava et al., 2020) |
Hoʻoikaika i ka mahiʻai pololei | (L. Deng et al., 2018; Kalischuk et al., 2019; Maimaitijiang et al., 2017) |
Hoʻokaʻawale a me ka mākaʻikaʻi ʻana o nā mea kanu | (Inoue, 2020; Kalischuk et al., 2019; Lopez- ´ Granados et al., 2016; Maimaitijiang et al., 2017; Melville et al., 2019; Moharana & Dutta, 2016) |
Ka hoʻohana ʻana i ka fertilizer | (L. Deng et al., 2018; Guan et al., 2019) |
Ka nānā ʻana i ka maloʻo | (Fawcett et al., 2020; Panday, Pratihast, et al., 2020; Su et al., 2018) |
Manaʻo biomass | (Bendig et al., 2014) |
Manao hua | (Inoue, 2020; Panday, Shrestha, et al., 2020; Tao et al., 2020) |
Hoʻemi pōʻino | (Negash et al., 2019) |
Mālama i nā holoholona hihiu a me ulu lāʻau | (Negash et al., 2019; Panday, Pratihast, et al., 2020) |
Ka loiloi o ke koʻikoʻi wai | (Inoue, 2020; J. Su, Coombes, et al., 2018; L. Zhang et al., 2019) |
Pest, weuweu, a me ka mai 'ike | (Gaˇ sparovi'c et al., 2020; Inoue, 2020; J. Su, Liu, et al., 2018; X. Zhang et al., 2019) |
Ma ka ʻaoʻao ʻē aʻe, ke kū nei nā drones i nā palena. ʻO ke komo ʻana o ka pailaka, ka mana mīkini, ka paʻa a me ka hilinaʻi, ka maikaʻi o nā sensor ma muli o ka uku
nā palena kaumaha, nā kumukūʻai hoʻokō, a me nā hoʻoponopono mokulele, aia i waena o lākou (C. Zhang & Kovacs, 2012). Hoʻohālikelike mākou i nā hemahema
o nā ʻenehana ʻike mamao paʻa lima ʻekolu ma ka Papa 2. ʻO nā ʻenehana ʻike mamao ʻē aʻe, e like me nā mea ʻike lepo, ʻaʻole i manaʻo ʻia o kēia haʻawina.
Nā hemahema o nā ʻenehana ʻike mamao paʻa lima.
Kamaʻāina mamao loea | Nā hāʻule | E hoʻomaopopo ' |
Drone (UAV) | Ke komo ʻana o ka pailaka; kiʻi ' maikaʻi (average); nā koina hoʻokō (awelika); paʻa, maneuverability, a hilinaʻi; hoʻohālikelike; mana mīkini; mana kaupalena nā kumu (ka lōʻihi o ka pākaukau); palena lōʻihi lele, collision a me ka cyberattacks; kaupalena kaumaha kaumaha; ʻikepili nui a me ka hoʻoili ʻikepili i kaupalena ʻia nā mea hiki; nele i ka hooponopono; nele i ke akamai, komo nui keakea i ke komo ana i nā drones mahiʻai; | (Bacco et al., 2018; Dawaliby et al., 2020; Hardin & Hardin, 2010; Hardin & Jensen, 2011; Lagkas et al., 2018; Laliberte et al., 2007; Laliberte & Rango, 2011; Manfreda et al., 2018, 2018; Nebiker et al., 2008; Puri et al., 2017; Velusamy et al., 2022; C. Zhang & Kovacs, 2012) |
ukali | ʻO ka uhi satellite manawa, palena spectral hoʻonā; pilikia i nā pilikia ʻike (eg, ao); Loaʻa ʻole a me ka māmā holo haʻahaʻa; hoʻonohonoho ʻana a me ka vignetting hopena i ka ʻikepili spatial pipiʻi hōʻiliʻili; lohi ka hāʻawi ʻana i ka ʻikepili manawa e hoʻopau i nā mea hoʻohana | (Aboutalebi et al., 2019; Cen et al., 2019; Chen et al., 2019; Nansen & Elliott, 2016; Panday, Pratihast, et al., 2020; Sai Vineeth et al., 2019) |
mokulele | ʻO nā kumukūʻai hoʻokipa kiʻekiʻe; hoʻonohonoho paʻakikī; nā koina mālama; unavailability of hilinaʻi mokulele, geometry o ka nā kiʻi; ʻikepili maʻamau ʻole loaa; nele i ka maʻalahi; nā pōʻino make; ʻikepili ʻike nā ʻokoʻa ma muli o ka haʻalulu; nā pilikia georeferencing | (Armstrong et al., 2011; ʻO Atkinson et al., 2018; Barbedo & Koenigkan, 2018; Kovalev & Voroshilova, 2020; Suomalainen et al., 2013; Thamm et al., 2013) |
Ma ke ʻano he ʻenehana multidisciplinary a multipurpose i ka mahiʻai, ua noiʻi ʻia nā drones mai nā ʻano like ʻole. No ka laʻana, ua nānā nā loea i nā noi drone i ka mahiʻai (Kulbacki et al., 2018; Mogili & Deepak, 2018), kā lākou hāʻawi ʻana i ka mahiʻai kūpono (Puri et al., 2017; Tsouros et al., 2019), kā lākou hoʻohui me nā mea ʻē aʻe. ʻenehana ʻokiʻoki (Al-Thani et al., 2020; Dutta & Mitra, 2021; Nayyar et al., 2020; Saha et al., 2018), a me nā hiki ke hoʻonui i kā lākou hiki ke hoʻokele a me ka ʻike (Bareth et al. , 2015; Suomalainen et al., 2014). No ka mea ua ulu nui ka noiʻi ʻana i nā noi drone i ka mahiʻai (Khan et al., 2021)), pono e hōʻuluʻulu i nā palapala e kū nei a hōʻike i ka ʻōnaehana naʻauao o ka domain. Eia kekahi, ma ke ʻano he kahua ʻenehana kiʻekiʻe me ka hoʻomau mau ʻana, pono e hana ʻia nā loiloi i kūkulu ʻia e hōʻuluʻulu i kēlā me kēia manawa i nā palapala e kū nei a ʻike i nā āpau noiʻi koʻikoʻi. I ka
i kēia lā, he liʻiliʻi nā loiloi e kūkākūkā ana i nā noi drone i ka ʻoihana mahiʻai. No ka laʻana, ʻo Mogili a me Deepak (2018) e loiloi pōkole i nā hopena o nādrones no ka nānā ʻana i nā mea kanu a me ka pīpī ʻana i nā pesticide. Ke alakaʻi nei ʻo Inoue (2020) i kahi loiloi o ka satellite a me ka hoʻohana drone i ka ʻike mamao i ka mahiʻai. Huli ka mea kākau i nā pilikia ʻenehana o ka hoʻohana ʻana i ka mahiʻai akamai a me nā haʻawina o nā satelite a me nā drones e pili ana i nā haʻawina hihia a me nā hana maikaʻi loa. ʻO Tsouros et al. (2019) hōʻuluʻulu i nā ʻano like ʻole o nā drones a me kā lākou noi nui i ka mahiʻai, e hōʻike ana i nā ʻano ʻikepili like ʻole a me nā ʻano hana. I kēia mau lā, ʻo Aslan et al. (2022) i ka loiloi piha o nā noi UAV i nā hana mahiʻai a hoʻopaʻa i ka pili o ka localization like a me ka palapala ʻāina no kahi UAV i loko o ka hale ʻōmaʻomaʻo. Diaz-Gonzalez et al. (2022) loiloi i nā noiʻi hou o ka hoʻohua ʻana i ka hua ma muli o nā ʻenehana aʻo mīkini like ʻole a mamao
ʻōnaehana ʻike. Ua hōʻike ʻia kā lākou ʻike he mea pono nā UAV no ka hoʻohālikelike ʻana i nā hōʻailona o ka lepo a ʻoi aku ka maikaʻi o nā ʻōnaehana satellite ma ke ʻano o ka hoʻonā spatial, ka manawa ʻike, a me ka maʻalahi. Basiri et al. (2022) hana i ka loiloi piha o nā ʻano ala like ʻole a me nā ala e lanakila ai i nā pilikia hoʻolālā ala no nā UAV multi-rotor i ka pōʻaiapili o ka mahiʻai pololei. Eia kekahi, ʻo Awais et al. (2022) hōʻuluʻulu i ka hoʻohana ʻana i ka ʻikepili ʻike mamao UAV i nā mea kanu e hoʻohālikelike i ke kūlana wai a hāʻawi i kahi synthesis hohonu o ka hiki ke hiki i ka UAV mamao sensing no ka noi kaumaha. ʻO ka hope, ʻo Aquilani et al. (2022) loiloi i nā ʻenehana mahiʻai mua i hoʻohana ʻia i nā ʻōnaehana holoholona e pili ana i ka pasture a hoʻoholo i ka maikaʻi o ka ʻike mamao i hoʻohana ʻia e nā UAV no ka loiloi biomass a me ka mālama ʻana i nā holoholona.
Eia kekahi, ua hōʻike ʻia nā hoʻāʻo e hoʻohana i nā UAV i ka nānā ʻana, ka nānā ʻana, a me ka hōʻiliʻili ʻana i nā holoholona.
ʻOiai ke hāʻawi nei kēia mau loiloi i nā ʻike hou a koʻikoʻi, ʻaʻole hiki ke ʻike ʻia kahi loiloi piha a me nā mea hou e pili ana i nā bibliometrics ma ka palapala, kahi e hōʻike ai i kahi ʻike maopopo. Eia kekahi, ua ʻōlelo ʻia i ka wā e ulu ai ka hana naʻauao ma kahi ʻepekema ʻepekema, lilo ia i mea koʻikoʻi no ka poʻe noiʻi e hoʻohana i nā ala loiloi quantitative e hoʻomaopopo i ke ʻano o ka ʻike o ka domain (Rivera & Pizam, 2015). Pēlā nō, ʻo Ferreira et al. (2014) i ʻōlelo ʻia i ka wā e ulu a paʻakikī ai nā ʻimi noiʻi, pono ka poʻe naʻauao e noʻonoʻo i ka ʻike i hana ʻia a hōʻiliʻili ʻia e hōʻike i nā hāʻawi hou, hopu i nā kuʻuna noiʻi a me nā ʻano, e ʻike i nā kumuhana i aʻo ʻia, a e ʻimi i ka ʻike ʻike ke kahua a me nā kuhikuhi noiʻi hiki. ʻOiai ʻo Raparelli lāua ʻo Bajocco (2019) i alakaʻi i kahi loiloi bibliometric e nānā i ka ʻike ʻike o nā noi drone i ka mahiʻai a me ka ulu lāʻau, noʻonoʻo kā lākou noiʻi i ka noiʻi naʻauao i paʻi ʻia ma waena o 1995 a me 2017, ʻaʻole ia e hōʻike i ka dynamics o kēia wahi wikiwiki. Eia kekahi, ʻaʻole i hoʻāʻo nā mea kākau e ʻike i nā haʻawina koʻikoʻi loa i ke kula, hui pū i nā palapala, a loiloi i ka ʻōnaehana naʻauao me ka hoʻohana ʻana i ka loiloi co-citation. ʻO ka hopena, pono e hōʻuluʻulu i nā palapala e hōʻike i ka foci noiʻi o kēia manawa, nā ʻano, a me nā wahi wela.
No ka hoʻopiha ʻana i kēia ʻike ʻike, hoʻohana mākou i ke ʻano quantitative methodology a me nā ʻano bibliometric ikaika e nānā i ke kūlana o ka noiʻi i kēia manawa ma ke kikowaena o nā drones a me ka mahiʻai. Ke hoʻopaʻapaʻa nei mākou ua hāʻawi ka haʻawina o kēia manawa i nā haʻawina i nā palapala e kū nei ma o ka nānā ʻana i kahi ʻenehana e kū nei i makemake nui ʻia i ka mahiʻai no ka mea hiki ke hoʻololi i kekahi mau ʻano o kēia ʻāpana. Ua ʻike ʻia ka pono o ka loiloi bibliometric o nā drones mahiʻai ma muli o ka ʻike i hoʻopuehu a ʻāpana ʻia i nā drones i loko o ka pōʻaiapili mahiʻai. Pēlā nō, pono e hoʻopili ʻia nā palapala e pili ana i nā drones mahiʻai, e noʻonoʻo ana i nā haʻawina koʻikoʻi e kūkulu i ke kumu o kēia kahua noiʻi. ʻO ka maikaʻi o ka loiloi pū kekahi me ka wehewehe ʻana i nā kumuhana noiʻi nui i hōʻike ʻia ma ka palapala. Ke noʻonoʻo nei i ka hiki ke hoʻololi ʻia o ka ʻenehana, manaʻo mākou e hāʻawi ana kahi ʻikepili hohonu i nā ʻike hou ma ka hoʻoholo ʻana i nā hana koʻikoʻi a me ka hōʻike ʻana i nā kumumanaʻo e pili ana i ka hiki o nā drones no ka mahiʻai.
No laila ke hoʻoikaika nei mākou e hoʻokō i kēia mau pahuhopu noiʻi:
- ʻO ka ʻike ʻana i nā paʻi koʻikoʻi me nā haʻawina koʻikoʻi i nā noi drone ma ke kahua o ka mahiʻai.
- ʻO ka hoʻopili ʻana i ka palapala, ka ʻike ʻana i ka ʻimi noiʻi, a me ka palapala ʻāina i nā haʻawina 'intellectual structure' ma muli o ka like like me ka hoʻohana ʻana i ka loiloi co-citation.
- ʻO ka hoʻomaopopo ʻana i ka ulu ʻana o nā loulou a me nā ʻupena kuhi i ka manawa ma waena o nā puke like ʻole ma ke kula a me ka ʻike ʻana i nā kuhikuhi noiʻi e hiki mai ana a me nā kumuhana wela.
Hoʻonohonoho ʻia ke koena o ka pepa penei: ʻo ka pauku 2 e wehewehe i ke ʻano hana a me nā ʻanuʻu o ka hōʻiliʻili ʻikepili; ʻO ka pauku 3 e hāʻawi i nā hopena o nā loiloi; a me ka pauku 4 e kūkākūkā ana i nā ʻike a hoʻopau me nā haʻawina noiʻi, nā hopena, a me nā kuhikuhi e hiki mai ana.
Ke Koʻikoʻo
Ma kēia noiʻi noiʻi o kēia manawa, hana mākou i kahi loiloi bibliometric e ʻimi i nā noi drone i ka mahiʻai. Hōʻike kēia ʻano quantitative i ka hoʻolālā naʻauao o ka ʻike ʻike (Arora & Chakraborty, 2021) a me ke kūlana o kēia manawa, nā kumuhana wela, a me nā kuhikuhi noiʻi e hiki mai ana e hiki ke noiʻi ʻia ma ka hoʻohana ʻana i kēia ʻano (Kapoor et al., 2018; Mishra et al. , 2017; A. Rejeb, Rejeb, et al., 2021b; A. Rejeb et al., 2021d; MA Rejeb et al., 2020). ʻO ka mea maʻamau, ʻike ʻia kahi loiloi bibliometric i nā palapala e noho nei e hōʻuluʻulu a wehe i nā ʻano huna o ka kamaʻilio kākau ʻana a me ka ulu ʻana o ke aʻo ʻana ma muli o nā helu a me nā ʻano makemakika, a pili ia i nā pūʻulu ʻikepili nui (Pritchard, 1969; Small, 1999; Tahai & Rigsby , 1998). Ma ka hoʻohana ʻana i nā bibliometrics, makemake mākou e hoʻomaopopo maikaʻi i nā paradigms e kū nei a me ka foci noiʻi e hāʻawi i ka domain e pili ana i ka like (Thelwall, 2008). Hāʻawi ka Bibliometrics i nā ʻike hou i kākoʻo ʻia e ka ikaika quantitative o ke ʻano hana (Casillas & Acedo, 2007). Ua alakaʻi mua nā loea he nui i nā haʻawina bibliometric i nā kāʻei pili, me ka mahiʻai, ka ʻike mamao, a me ka hoʻololi kikohoʻe (Armenta-Medina et al., 2020; Bouzembrak et al., 2019; A. Rejeb, Treiblmaier, et al., 2021; Wamba & Queiroz, 2021; Wang et al., 2019).
Ka hoʻopili ʻōlelo
Hōʻike ka hōʻike ʻana i nā ʻike like ʻole i kahi kahua noiʻi i hāʻawi ʻia. ʻO ka mea mua, kōkua ia e hōʻike i nā mea kākau koʻikoʻi a me nā puke e hāʻawi i kahi kahua noiʻi i hāʻawi ʻia a hana i kahi hopena koʻikoʻi (Gundolf & Filser, 2013). ʻO ka lua, hiki ke ʻike ʻia ke kahe o ka ʻike a me nā loulou kamaʻilio ma waena o nā mea kākau. ʻO ka mea hope loa, ma ka ʻimi ʻana i nā loulou ma waena o nā hana i ʻōlelo ʻia a me ka haʻi ʻana, hiki i kekahi ke ʻimi i nā loli a me ka ulu ʻana o kahi kahua ʻike i ka manawa (Pournader
et al., 2020). Hōʻike ka helu helu kiʻekiʻe o kahi paʻi i kona pili a me nā haʻawina nui i ke kahua noiʻi (Baldi, 1998; Gundolf & Filser, 2013; Marinko, 1998). E kōkua pū ana ka helu ʻana i nā puke i ka ʻike ʻana i nā hana kūpono a me ka nānā ʻana i ko lākou kaulana a me ka holomua ʻana i ka manawa.
Ka hoʻokaʻawale ʻana i ka ʻōlelo hoʻopaʻa palapala
He ʻano waiwai nui ka ʻimi ʻana i nā pilina ma waena o nā puke a hōʻike i ke ʻano o ka naʻauao o kahi māla (Nerur et al., 2008). Ma nā huaʻōlelo ʻē aʻe, ma ka ʻike ʻana i nā puke i ʻōlelo ʻia a me ko lākou pili ʻana, ʻo ke ala e hui pū ai i nā paʻi i loko o nā puʻupuʻu noiʻi ʻokoʻa kahi e kaʻana like mau ai nā paʻi i loko o kahi hui (McCain, 1990; Small, 1973). He mea koʻikoʻi ka haʻi ʻana ʻaʻole like ka manaʻo o nā ʻike o nā paʻi
hui pū a ʻae kekahi i kekahi; Aia nā puke i ka hui like ma muli o ke kumuhana like, akā hiki ke loaʻa nā manaʻo kūʻē.
ʻIkepiliʻikepili a me ka hoʻopili
Ma hope o ke kaʻina hana i manaʻo ʻia e White and Griffith (1981), ua hana mākou i kahi ʻimi piha o nā ʻatikala puke e uhi i ke kahua noiʻi holoʻokoʻa o nā noi drone i ka mahiʻai, e hahai ana i nā pae ʻelima:
- ʻO ka hana mua, ʻo ia ka ʻohi ʻikepili. Ua koho ʻia ʻo Scopus ma ke ʻano he ʻikepili piha loa a hilinaʻi me nā hopena maʻamau. Ua kiʻi ʻia ka meta-data o nā puke e pili ana i nā noi drone āpau i ka mahiʻai. A laila, kālele mākou i nā ʻatikala i koho ʻia, e wehe ana i nā ʻatikala ma waho o ke kumuhana.
- Ua kālailai mākou i nā palapala a ʻike i nā huaʻōlelo koʻikoʻi i hoʻohana ʻia ma ka wahi noiʻi.
- Me ka hoʻohana ʻana i ka ʻikepili ʻōlelo, ua ʻimi mākou i ka pilina ma waena o nā mea kākau a me nā palapala e hōʻike ai i nā kumu hoʻohālike kumu. Ua ʻike pū mākou i nā mea kākau koʻikoʻi a me nā paʻi me nā haʻawina nui i ke kahua o nā drones mahiʻai.
- Ua hana mākou i kahi loiloi co-citation e hui pū i nā puke like i loko o nā pūʻulu.
- ʻO ka hope, ua kālailai mākou i nā pilina a me nā pilina ma waena o nā ʻāina, nā ʻoihana, a me nā puke pai e hōʻike i ka ʻoihana hui.
Ka ʻike ʻana i nā huaʻōlelo hulina kūpono
Ua hoʻohana mākou i kēia mau kaula hulina no ka hōʻuluʻulu ʻikepili: (drone* A I ʻole “kaʻa lele lele ʻole” A i ʻole uav* A i ʻole “pūnaewele mokulele manuahi ʻole.” OR uas A I ʻole "mau mokulele hoʻokele mamao”) A (mahiʻai A mahiʻai OR mahiʻai OR mea mahiʻai). Ua mālama ʻia ka ʻimi i ka mahina ʻo Kepakemapa 2021. Ua loaʻa i nā drones kekahi mau inoa, me ka UAV, UAS, a me nā mokulele hoʻokele mamao (Sah et al., 2021). Ua ʻike ʻia nā huaʻōlelo hulina kikoʻī e pili ana i ka mahiʻai ma muli o ke aʻo ʻana o Abdollahi et al. (2021). No ka maopopo a me ka maopopo, ua hāʻawi ʻia ka nīnau pololei a mākou i hoʻohana ai ma Appendix 1. Ma hope o kahi kaʻina hana hoʻomaʻemaʻe ʻikepili, hana mākou i kahi faila kikokikona i hoʻouka ʻia ma BibExcel, kahi mea hana maʻamau no ka hoʻopili ʻana a me ka nānā ʻana i ka co-citation. Hāʻawi kēia mea hana i ka pilina maʻalahi me nā polokalamu ʻē aʻe a hāʻawi i kahi pae koʻikoʻi o ke kūʻokoʻa i ka lawelawe ʻana a me ka nānā ʻana. Ua hoʻohana ʻia ʻo VOSviewer version 1.6.16 e nānā i nā ʻike a hoʻopuka i nā pūnaewele bibliometric (Eck & Waltman, 2009). Hāʻawi ʻo VOSviewer i kahi ʻano o ka intuitive visualization, ʻoi loa no ka nānā ʻana i nā palapala bibliometric (Geng et al., 2020). Eia kekahi, kōkua ia i ka hāʻawi ʻana i nā hopena ʻike maʻalahi e kōkua i ka hoʻomaopopo maikaʻi ʻana i nā hopena (Abdollahi et al., 2021). Ke hoʻohana nei i nā kaula hulina e like me ka mea i ʻōlelo ʻia ma luna, ua hōʻiliʻili mākou a mālama i nā puke kūpono āpau. Ua loaʻa i nā hualoaʻa mua he 5,085 mau palapala. No ka hōʻoia ʻana i ka maikaʻi o ka laʻana i koho ʻia, ua noʻonoʻo ʻia nā ʻatikala puke puke i nānā ʻia e nā hoa i loko o ka noiʻi, no laila e kāpae ʻia nā ʻano palapala ʻē aʻe, e like me nā puke, nā mokuna, nā kaʻina kūkā, a me nā memo hoʻoponopono. I loko o ke kaʻina hana hoʻopaʻa ʻana, ua kāʻili ʻia nā mea pili ʻole (ʻo ia hoʻi, ma waho o ke ʻano o kēia hana), ʻoi aku (ʻo ia hoʻi, nā kope i hoʻokumu ʻia mai ka papa kuhikuhi pālua), a me nā puke ʻōlelo Pelekania ʻole. ʻO kēia kaʻina hana i hoʻokomo ʻia ai nā palapala 4,700 i ka loiloi hope.
ʻIke a kūkākūkā
No ka hoʻomaka ʻana, ua loiloi mākou i nā hoʻomohala o ka hoʻopuka paʻi ʻana i nā puke o kēia manawa e pili ana i nā drones mahiʻai. Hōʻike ʻia ka māhele manawa o ka noiʻi naʻauao ma ka Fig. no laila, ua hoʻoholo mākou e hoʻokaʻawale i ka wā loiloi i ʻelua mau pae like ʻole. Ke kuhikuhi nei mākou i ka manawa ma waena o 1 a me 2011 ma ke ʻano he kahua kūkulu, kahi i paʻi ʻia ʻehiku mau pepa i kēlā me kēia makahiki. Ua kapa ʻia ka manawa ma hope o 30 i ka ulu ulu ʻana mai ka noiʻi ʻana i nā noi drone i ka mahiʻai i ʻike i kahi piʻi nui i kēia manawa. Ma hope o 1990, ʻo ka hoʻonui nui ʻana o nā paʻi e hōʻoia ana i ka ulu ʻana o ka hoihoi i waena o nā mea noiʻi, e hōʻike ana hoʻi ua hoʻohana ʻia nā drones i ka ʻike mamao a hoʻohana ʻia i ka mahiʻai kūpono (Deng et al., 2010; Maes & Steppe, 2010; Messina & Modica, 2010 ). Ma keʻano kikoʻī, ua piʻi ka helu o nā paʻi mai 2018 i 2019 a i 2020 i 108 a piʻi i ka 2013 i 498. Ua paʻi ʻia ka huina o 2018 mau ʻatikala ma waena o Ianuali a me waena o Sepatemaba 1,275. ʻoiai ke hōʻike nei kēia manawa i nā subtleties hou a koʻikoʻi o nā drones mahiʻai.
Kānāwai huaʻōlelo
He hopena koʻikoʻi ko nā huaʻōlelo a nā mea kākau e koho ai no ka paʻi ʻana i ke ʻano o ka hōʻike ʻia ʻana o ka pepa a me ke ʻano o ke kamaʻilio ʻana i loko o nā kaiāulu ʻepekema. Hoʻomaopopo lākou i nā kumuhana koʻikoʻi o ka noiʻi a hoʻoholo i kona hiki ke ulu a hāʻule paha (Day & Gastel, 1998.; Kim et al., 2016; Uddin et al., 2015). ʻO ka nānā ʻana i nā huaʻōlelo, kahi mea hana e hōʻike i nā ʻano noiʻi ākea a me nā kuhikuhi, e pili ana i ka hōʻuluʻulu ʻana o nā huaʻōlelo o nā paʻi pili āpau i kahi kikowaena (Dixit & Jakhar, 2021). Ma ka haʻawina o kēia manawa, ua māhele mākou i nā huaʻōlelo i hōʻuluʻulu ʻia i ʻelua pūʻulu (ʻo ia hoʻi, a hiki i 2010 a me 2011–2021) e ʻimi i nā kumuhana kaulana loa. Ma ka hana ʻana i kēia, hiki iā mākou ke ʻimi i nā huaʻōlelo koʻikoʻi ma nā pūʻulu ʻelua a hōʻoia i ka hopu ʻana i nā ʻikepili pono āpau. No kēlā me kēia hoʻonohonoho, hōʻike ʻia nā huaʻōlelo he ʻumi ma ka Papa 3. Ua hoʻopau mākou i nā mea like ʻole ma o ka hoʻohui ʻana i nā huaʻōlelo semantically identical, e like me "drone" a me "drones" a i ʻole, "Internet of Things" a me "IoT."
Hōʻike ka Papa 3 he huaʻōlelo i hoʻohana pinepine ʻia ka "kaʻa lewa ʻole" e like me ka "drone" a me "unmanned aerial system" i nā manawa ʻelua. Eia kekahi, ʻoi aku ka maikaʻi o ka "manaʻo mamao," "mahiʻai kūpono," a me ka "mahiʻai" i nā manawa ʻelua. I ka manawa mua, ua helu ʻia ka "ʻoihana mahiʻai" i ka lima, a ʻo ia ka lua i ka lua o ka manawa, e hōʻike ana i ka ulu ʻana o nā drones i mea koʻikoʻi i ka hoʻokō ʻana i ka mahiʻai kūpono e hiki ai iā lākou ke nānā.
ʻoi aku ka wikiwiki, ʻoi aku ka maʻalahi a me ka maʻalahi o ka hoʻokō ʻana i ka hoʻohālikelike ʻana me nā ʻōnaehana mamao a me ka honua. Eia kekahi, hiki iā lākou ke pīpī i ka nui pololei o ka hoʻokomo (e laʻa, ka wai a i ʻole nā pesticides) i ka wā e pono ai (Guo et al., 2020; Inoue, 2020; Panday, Pratihast, et al., 2020).
Ka papa inoa o nā huaʻōlelo i hoʻohana pinepine ʻia.
Rank | 1990-2010 | No nā hanana | 2011-2021 | No nā hanana |
1 | lewa holo ʻole kaa | 28 | unmanned kaʻa lewa | 1628 |
2 | ʻikeʻole | 7 | pololei mahiai | 489 |
3 | mahiai | 4 | ʻikeʻole | 399 |
4 | lele lewa | 4 | drone | 374 |
5 | pololei mahiai | 4 | unmanned ʻōnaehana lewa | 271 |
6 | lewa holo ʻole | 4 | mahiai | 177 |
7 | hyperspectral mīkiniʻimi | 3 | haʻawina hohonu | 151 |
8 | neural hana latike | 2 | mīkini palapala he | 149 |
9 | lele kūʻokoʻa | 2 | nā mea kanu Index | 142 |
10 | kope | 2 | Pūnaewele o na mea | 124 |
ʻO kekahi hiʻohiʻona hoihoi ka hiki ʻana o nā ʻenehana hoʻohui. I ka pae mua, ʻo "Hyperspectral Sensor" a me nā "network neural artificial" (ANN) i waena o nā huaʻōlelo he ʻumi. Ua hoʻololi ke kiʻi Hyperspectral i ke kiʻi kuʻuna ma o ka hōʻiliʻili ʻana i nā kiʻi nui ma nā lōʻihi nalu like ʻole. I ka hana ʻana pēlā, hiki i nā mea ʻike ke hōʻiliʻili i ka ʻike kikoʻī a me ka spectral i ka manawa like e like me ke kiʻi multispectral, spectroscopy, a me nā kiʻi RGB (Adao˜ et al.,
2017). ʻO ka loaʻa ʻana o "ANN" i ka pae mua a me ka "aʻo hohonu" (DL) a me ka "aʻo ʻana i ka mīkini" (ML) i ka lua e hōʻike ana i ka hapa nui o nā hana i paʻi ʻia i ka nānā ʻana i ka hiki o nā ʻenehana AI no ka drone- ʻoihana mahiʻai. ʻOiai hiki i nā drones ke lele kūʻokoʻa, koi lākou i ke komo ʻana o kahi pailaka, e hōʻike ana i kahi haʻahaʻa haʻahaʻa o ka ʻike. Eia nō naʻe, hiki ke hoʻopau ʻia kēia pilikia ma muli o ka holomua o nā ʻenehana AI, hiki ke hāʻawi i ka ʻike kūlana maikaʻi aʻe a me ke kākoʻo hoʻoholo kūʻokoʻa. Hoʻolako ʻia me AI, hiki i nā drones ke pale aku i ka hui ʻana i ka wā hoʻokele, hoʻomaikaʻi i ka ʻāina a me ka hoʻokele ʻana i nā mea kanu (Inoue, 2020), a hōʻemi i ka hana a me ke kaumaha no nā kānaka (BK Sharma et al., 2019).
Ma muli o ko lākou maʻalahi a me ka hiki ke mālama i ka nui o nā ʻikepili nonlinear, ʻo nā ʻenehana AI nā ala kūpono e kālailai i ka ʻikepili i lawe ʻia e nā drones a me nā ʻōnaehana mamao a me nā ʻōnaehana honua no ka wānana a me ka hoʻoholo ʻana (Ali et al., 2015; Inoue, 2020). Eia kekahi, ʻo ka hele ʻana o "IoT" i ka lua o ka manawa e hōʻike ana i kāna hana e kū nei i ka mahiʻai. Ke hoʻololi nei ʻo IoT i ka mahiʻai ma o ka hoʻopili ʻana i nā ʻenehana ʻē aʻe, me nā drones, ML, DL, WSN, a me nā ʻikepili nui. ʻO kekahi o nā pōmaikaʻi koʻikoʻi o ka hoʻokō ʻana iā IoT ʻo kona hiki ke hoʻohui maikaʻi a me ka hoʻohui ʻana i nā hana like ʻole (ka loaʻa ʻana o ka ʻikepili, ka ʻikepili a me ka hana ʻana, ka hoʻoholo ʻana, a me ka hoʻokō) i ka manawa maoli (Elijah et al., 2018; Feng et al. , 2019; Muangprathub et al., 2019). Eia kekahi, ua manaʻo ʻia nā drones i nā mea hana pono no ka hopu ʻana i ka ʻikepili e pono ai no ka helu ʻana i ka ikaika o nā mea kanu a me nā waiwai mea kanu (Candiago et al., 2015). Hōʻike ka Fig. 2a a me 2b i nā huaʻōlelo hui like ʻole no nā manawa ʻelua.
Nā mea kākau mana
Ma kēia ʻāpana, hoʻoholo mākou i nā mea kākau koʻikoʻi a nānā i ke ʻano e hiki ai i nā ʻupena huaʻōlelo mea kākau ke nānā a hoʻonohonoho i nā palapala o kēia manawa. Hōʻike ka Fig. 3 i ka overlay chronological o nā mea noiʻi āpau me ka helu kiʻekiʻe o nā huaʻōlelo. Hōʻike ka pālākiō kala i ka ʻokoʻa makahiki o nā ʻōlelo a nā mea kākau. Nānā mākou i ke ʻano o nā mea noiʻi i hoʻopuka i nā haʻawina e pili ana i nā drones mahiʻai ma o ka hoʻohana ʻana i ka paepae o ka liʻiliʻi o 50 mau huaʻōlelo a me ʻumi paʻi. I waho o
12,891 mau mea kākau, 115 wale nō i hālāwai i kēia kūlana. Hōʻike ka papa 4 i nā mea kākau koʻikoʻi he ʻumi, i hoʻokaʻawale ʻia e ka nui o nā huaʻōlelo. ʻO Lopez- Granados F. ke alakaʻi nei i ka papa inoa me 1,963 mau huaʻōlelo, a ukali ʻia e Zarco-Tejada PJ me 1,909 mau huaʻōlelo.
Ka papa inoa o nā mea kākau i ʻōlelo ʻia.
kiʻekiʻe | Ka mea kākau Ke | Nā palapala |
1 | Lopez-Granados ´ F. | 1,963 |
2 | Zarco-Tejada PJ | 1,909 |
3 | Pena ˜ JM | 1,644 |
4 | Torres-S´ anchez J. | 1,576 |
5 | ʻO Fereres E | 1,339 |
6 | Remondino F | 1,235 |
7 | ʻO Bolten A | 1,160 |
8 | ʻO Bareth G | 1,155 |
9 | Berni JA | 1,132 |
10 | de Castro AI | 1,036 |
I ka wā e pili ana i nā puke pākahi, ʻo Zhang a me Kovacs (2012) ʻatikala ka haʻawina nui i paʻi ʻia ma Precision Agriculture. Ma ʻaneʻi, ua loiloi nā mea kākau i ka noi ʻana o UAS i ka mahiʻai pololei. Hōʻike nā ʻike o kā lākou noiʻi ʻana he pono e holomua i ka hoʻolālā platform, hana, hoʻohālikelike i ka georeferencing kiʻi, a me ka holo ʻana o ka ʻike e hoʻolako i nā mea mahiʻai me nā huahana hopena hilinaʻi. Hoʻohui ʻia, paipai lākou i ka hoʻopili ikaika ʻana i ka mea mahiʻai, ʻoi aku hoʻi i ka hoʻolālā kahua, kiʻi kiʻi, a me ka wehewehe ʻikepili a me ka nānā ʻana. ʻO ka mea nui, ʻo kēia haʻawina kekahi o nā mea mua i hōʻike i ke koʻikoʻi o ka UAV i ka palapala ʻāina, ka palapala ʻāina ikaika, ke ana ʻana i nā mea kemika, ka nānā ʻana i ke koʻikoʻi o nā mea kanu, a me ka loiloi i nā hopena o nā mea kanu i ka ulu ʻana o nā mea kanu. ʻO nā pilikia e pili ana i ka ʻenehana pū kekahi me nā kumukūʻai pāpā, ka hiki ke sensor, ke kūpaʻa a me ka hilinaʻi o ka paepae, ka nele o ka hoʻohālikelike ʻana, a me ke kaʻina hana maʻamau e nānā i ka nui o ka ʻikepili.
Ka hoʻopili ʻōlelo
Hōʻike ka ʻatikala ʻōlelo i ke aʻo ʻana i ka mana o nā ʻatikala, ʻoiai e pili ana i nā kahe (e laʻa, ka manaʻo kuhi, ka ʻōlelo pilikino) i manaʻo ʻia kekahi o nā mea hana maʻamau no ka loiloi hopena (Osareh, 1996; A. Rejeb et al., 2022; Sarli et al., 2010). Hōʻike pū nā ʻōlelo i ke koʻikoʻi a me ka ikaika o nā haʻawina o nā pepa i ka palapala e pili ana i kahi kumuhana kūikawā (R. Sharma et al., 2022). Ua alakaʻi mākou i kahi hōʻuluʻulu manaʻo no ka hoʻoholo ʻana i nā haʻawina koʻikoʻi e pili ana i nā drones mahiʻai a hōʻuluʻulu i nā ʻike. Hōʻike ka Papa 5 i ka papa inoa o nā pepa koʻikoʻi he ʻumikumamālima no nā manawa 1990–2010 a me 2011–2021. ʻO nā ʻatikala a Berni et al. ʻO (2009)b a me Austin (2010) ka mea i ʻōlelo ʻia i ka makahiki 1990 a me 2010, me 831 a me 498 mau huaʻōlelo. Berni et al. (2009)b hōʻike i ka hiki ke hoʻomohala i nā huahana remotesensing quantitative ma o ka UAV hoʻokumu ʻia helicopter i hoʻolako ʻia me nā mea ʻike kiʻi wela a me nā narrowband multispectral imaging. Ke hoʻohālikelike ʻia me nā mea ʻike lewa maʻamau, hiki i kahi ʻōnaehana UAV kumu kūʻai haʻahaʻa no ka mahiʻai ke hoʻokō i nā helu hoʻohālikelike o nā ʻāpana biophysical o nā mea kanu, inā ʻaʻole maikaʻi. ʻO ke kumukūʻai kūpono a me ka maʻalahi o ka hana, me nā hoʻonā kiʻekiʻe spectral, spatial, a me ke kino i loaʻa i ka manawa hoʻololi wikiwiki, hāʻawi i nā UAV i kūpono no ka nui o nā noi e koi ana i ka hoʻokele manawa koʻikoʻi, me ka hoʻonohonoho ʻana i ka wai, a me ka mahiʻai pololei. ʻO ka pepa mai Berni et al. (2009)b ka mea nui no ka mea ua hoʻohui maikaʻi ʻo ia i kahi kahua ʻēheu ʻēheu unmanned a me nā mea ʻike kikohoʻe a me ka wela me nā mīkini calibration pono no nā noi mahiʻai. ʻO ka lua o ka puke i ʻōlelo ʻia he puke i kākau ʻia e Austin (2010), nāna i kūkākūkā i nā UAV mai ka hoʻolālā, hoʻomohala ʻana, a me nā hiʻohiʻona deployment. Ma ka mahiʻai, kākoʻo nā UAV i ka nānā ʻana i nā mea kanu ma o ka ʻike mua ʻana i nā maʻi ma o ka hoʻololi ʻana i ka waihoʻoluʻu o nā hua, hoʻomaʻamaʻa i ka lūlū hua a me ka pīpī ʻana, a me ka nānā ʻana a me ka hoʻokele ʻana i nā holoholona.
ʻO nā haʻawina o Sullivan et al. (2007), Lumme et al. (2008), a me Gokto ¨ ǧan et al. (2010) hoʻopau i ka papa inoa o nā ʻatikala ʻumikūmālima kiʻekiʻe loa. Hōʻike kēia mau ʻatikala i ka hoʻomohala ʻana o nā ʻōnaehana UAV e kākoʻo i ka mahiʻai. Hāʻawi lākou i nā hoʻonā i nā pilikia like ʻole, e like me ka nānā ʻana a me ka nānā ʻana i nā mea kanu, ka nānā ʻana a me ka hoʻokele weed, a me ke kākoʻo hoʻoholo. Manaʻo a kūkākūkā pū lākou i ka hiki o UAV e hoʻonui i ka maikaʻi o ka laʻana a kōkua i ka poʻe mahiʻai i ka hoʻolālā pololei a me ka maikaʻi.
hoʻolālā kanu. ʻElua mau pepa i kākau ʻia e Berni (Berni et al., 2009b; Berni et al., 2009a), e hōʻike ana i kona hopena koʻikoʻi i ka noiʻi pili i ka drone. ʻO ka pepa mai Zarco-Tejada et al. ʻO (2014) kekahi o nā haʻawina paionia e hōʻike i ka pono e hoʻohana i nā kiʻi UAV haʻahaʻa i ka helu kiʻekiʻe o ka lāʻau.
Ka papa inoa o nā puke i ʻōlelo ʻia.
Rank | Mai 1990 a i 2010 | Mai 2011 a i 2021 | ||
Palapala | Kāhea | Palapala | Kāhea | |
1 | (Berni et al., 2009b) | 831 | (C. Zhang & Kovacs, 2012) | 967 |
2 | (Austin, 2010) | 498 | (Nex & Remondino, 2014) | 893 |
3 | (Hunt et al., 2010) | 331 | (Floreano & Wood, 2015) | 552 |
4 | (SR Herwitz et al., 2004) | 285 | (Hossein Motlagh et al., 2016) | 391 |
5 | (CCD Lelong et al., 2008) | 272 | (Shakhatreh et al., 2019) | 383 |
6 | (Berni et al., 2009b) | 250 | (Ma et al., 2017) | 373 |
7 | (Grenzdorfer ¨ et al., 2008) | 198 | (Bendig et al., 2014) | 360 |
8 | (Hrabar et al., 2005) | 175 | (Zarco-Tejada et al., 2014) | 347 |
9 | (Y. Huang et al., 2009) | 129 | (Ad˜ ao et al., 2017) | 335 |
10 | (Schmale III et al., 2008) | 119 | (Honkavaara et al., 2013a) | 331 |
11 | (Abd-Elrahman et al., 2005) | 79 | (Candiago et al., 2015) | 327 |
12 | (Techy et al., 2010) | 69 | (Xiang & Tian, 2011) | 307 |
13 | (Sullivan et al., 2007) | 51 | (Matese et al., 2015) | 303 |
14 | (Lumme et al., 2008) | 42 | (Gago et al., 2015) | 275 |
15 | (Gokto ¨ ǧan et al., 2010) | 40 | (Aasen et al., 2015a) | 269 |
I ka lua o ka manawa (2011–2021), ʻo ka noiʻi ʻana a Zhang and Kovacs (2012) a me Nex and Remondino (2014) i hopena i nā puke i ʻōlelo pinepine ʻia. Hoʻopaʻapaʻa ʻo Zhang a me Kovacs (2012) hiki i ka mahiʻai pololei ke pōmaikaʻi mai ka hoʻokō ʻana i nā ʻenehana geospatial a me nā mea ʻike, e like me nā ʻōnaehana ʻike honua, GPS, a me ka ʻike mamao, e hopu i nā ʻano like ʻole o ke kula a mālama iā lākou ma ka hoʻohana ʻana i nā hoʻolālā ʻokoʻa. Ma ke ʻano he mea hoʻololi pāʻani i ka mahiʻai pololei, ua hoʻolaha ka lawe ʻana i nā drones i kahi makahiki hou i ka ʻike mamao, hoʻomaʻamaʻa i ka nānā ʻana i ka lewa, hopu i ka ʻikepili ulu ulu, nā kūlana lepo, a me nā wahi hoʻoheheʻe. He mea nui ka loiloi o Zhang a me Kovacs (2012) no ka mea ua hāʻawi ʻo ia i nā ʻike i nā UAV ma ka hōʻike ʻana i nā hoʻohana a me nā pilikia o kēia mau mea i ka nānā ʻana i ke kaiapuni a me ka mahiʻai pololei, e like me nā palena a me nā kāmela, nā pilikia hoʻoili ʻikepili, ke komo ʻana o ka mahiʻai, a me nā lula mokulele. . ʻO ka lua
ʻO ka haʻawina i haʻi ʻia mai Nex and Remondino (2014) nānā i ke kūlana o ke akamai o nā UAV no ka hopu ʻana, ka hana ʻana, a me ka nānā ʻana i nā kiʻi honua.
Ua hōʻike pū kā lākou hana i kahi ʻike nui o nā paepae UAV, nā noi, a me nā hihia hoʻohana, e hōʻike ana i nā holomua hou loa i ka hoʻoili kiʻi UAV. Ma ka mahiʻai, hiki i ka poʻe mahiʻai ke hoʻohana i nā UAV e hana i nā hoʻoholo kūpono no ka loaʻa ʻana o ke kumukūʻai a me ka mālama manawa, loaʻa i kahi moʻolelo wikiwiki a pololei o nā pohō, a manaʻo i nā pilikia e hiki mai ana. Ma ka ʻokoʻa i nā paepae lewa maʻamau, hiki i nā UAV ke ʻoki i nā koina hana a hōʻemi i ka pōʻino o ke komo ʻana i nā wahi paʻakikī ʻoiai e mālama mau ana i ka hiki ke pololei. Hōʻuluʻulu kā lākou pepa i nā pono like ʻole o nā UAV, e pili ana i ka pololei a me ka hoʻonā.
Ma waena o ke koena he ʻumikumamākolu mau paʻi i haʻi ʻia ma waena o 2011 a me 2021, ua ʻike mākou i ka ʻoi aku ka nui o ka noiʻi e pili ana i nā noi drone i nā misionari kiʻi (Bendig et al., 2014; Ma et al., 2017; Zarco-Tejada et al., 2014) , ka mahiʻai pololei (Candiago et al., 2015; Honkavaara et al., 2013a), nā mea kanu pono (Matese et al., 2015), ka loiloi wai (Gago et al., 2015), a me ka nānāʻana i nā mea kanu (Aasen et al. , 2015a). I nā makahiki mua, ua nānā nā mea noiʻi
ʻoi aku ka nui o ka hoʻomohala ʻana i nā kumu kūʻai haʻahaʻa, māmā, a me nā ʻōnaehana UAV no ka mahiʻai; ʻO nā noiʻi hou loa i kālele nui ʻia i nā loiloi o nā noi UAV no ka mahiʻai a me ke ana ʻāina. Ma ka hōʻuluʻulu manaʻo, hōʻike kēia ʻano loiloi ua hāʻawi ka hapa nui o nā puke koʻikoʻi i nā loiloi o nā noiʻi mua e loiloi i ke kūlana ʻepekema a me ka ʻenehana o nā UAV i kēia manawa a hoʻomohala i nā ʻōnaehana UAV e kākoʻo i ka mahiʻai pololei. ʻO ka mea mahalo, ʻaʻole mākou i ʻike i nā haʻawina i hoʻohana i ka empirical
nā ʻano hana a i ʻole nā haʻawina hoʻonaʻauao wehewehe, ʻo ia ka mea i loaʻa i kahi ākea ʻike koʻikoʻi a pono e noiʻi hou aku i kēia kumuhana.
Ka hoʻokaʻawale ʻana i ka helu ʻana
Wahi a Gmür (2006), ʻike ʻia ka hoʻopaʻa ʻōlelo ʻana i nā puke like a hoʻopili iā lākou. ʻO ka nānā pono ʻana i kahi puʻupuʻu hiki ke hōʻike i kahi kahua noiʻi maʻamau ma waena o nā paʻi. Ke noiʻi nei mākou i ka hui pū ʻana o nā puke e pili ana i nā drones mahiʻai e hōʻike i nā kumuhana pili a ʻike i nā ʻano naʻauao o nā puke. Ma kēiaʻano, ua manaʻo ʻo Small (1973) i ka hoʻohana ʻana i ka loiloi cocitation e aʻo i ka noiʻi koʻikoʻi a me ka seminal.
i loko o kahi hoʻopaʻi. No ka kaupalena ʻana i ka hoʻonohonoho ʻana i nā ʻatikala nui loa (Goyal & Kumar, 2021), hoʻonoho mākou i ka paepae co-citation o 25, ʻo ia hoʻi, ʻelua mau ʻatikala i hui pū ʻia ma nā papa kuhikuhi o 25 a ʻoi aku paha nā paʻi ʻokoʻa. Ua mālama ʻia ka hui ʻana me ka liʻiliʻi liʻiliʻi puʻupuʻu 1 a me ka ʻole o ke ʻano no ka hoʻohui ʻana i nā puʻupuʻu liʻiliʻi me nā pūʻulu nui. ʻO ka hopena, ua hoʻokumu ʻia nā pūʻulu ʻeono ma muli o ka like o nā haʻawina a me ko lākou ʻano naʻauao. Hōʻike ka papa 6 i ka māhele ʻana o nā puke i kēlā me kēia pūʻulu.
Hui 1: Aia i loko o kēia pūʻulu he ʻumikūmāwalu mau palapala i paʻi ʻia ma hope o ke kūkākūkā ʻana o nā puke ma kēia pūʻulu i ke kuleana o nā drones i ke kākoʻo ʻana i ka nānā ʻana i ke kaiapuni, ka hoʻoponopono ʻana i nā mea kanu, a me ka mālama ʻana i ka mauʻu. Eia kekahi laʻana, Manfreda et al. (2018) hāʻawi i kahi hiʻohiʻona o ka noiʻi a me ka hoʻokō ʻana o ka UAV i ka nānā ʻana i nā kaiaola mahiʻai kūlohelohe a hoʻopaʻapaʻa e hāʻawi ka ʻenehana i ka mana nui e hoʻomaikaʻi nui i ka nānā ʻana i ke kaiapuni a hōʻemi.
ka ʻokoʻa ma waena o ka mākaʻikaʻi kahua a me ka ea maʻamau a me ka ʻike mamao. Hiki ke hana ʻia kēia ma ka hāʻawi ʻana i ka mana hou no ka hoʻomaikaʻi ʻana i ke kino a me nā ʻike kikoʻī i nā wahi nui ma ke ala kūpono. Hiki i nā UAV ke ʻike mau i ke kaiapuni a hoʻouna i ka ʻikepili i loaʻa i nā hui naʻauao, kikowaena/decentralized e hoʻokele i nā mea ʻike e ʻike i nā pilikia e hiki mai ana, e like me ka nele o ka maʻi a i ʻole ka ʻike wai (Padua ´ et al., 2017). Adao ˜ et al. (2017) manaʻo maikaʻi nā UAV no ka loiloi ʻana i nā kūlana o nā mea kanu ma o ka hopu ʻana i ka nui o ka ʻikepili maka e pili ana i ke kūlana wai, ka helu biomass, a me ka loiloi ikaika. Hiki ke hoʻokomo koke ʻia nā mea ʻike i kau ʻia ma UAV i nā kūlana kaiapuni kūpono e ʻae i ka hopu ʻana i ka ʻikepili mamao mamao (Von Bueren et al., 2015). Ma o nā UAV, hiki i ka poʻe mahiʻai ke hoʻokō i nā hana mahiʻai i loko ma o ka loaʻa ʻana o nā ana mai nā wahi a pau i loko o nā ʻāpana ʻekolu o nā wahi mahiʻai i loko (e laʻa, nā hale ʻōmaʻomaʻo), no laila e hōʻoiaʻiʻo ai i ka mālama ʻana i ke aniau a me ka nānā ʻana i nā mea kanu (Roldan ´ et al. ., 2015). Ma ka pōʻaiapili o ka pololei
ʻO ka mahiʻai, ka hoʻoholo ʻana i ka hoʻokele ʻana i nā mea kanu e pono ai i ka ʻikepili huaʻai kūpono a hilinaʻi me ka hoʻonā ʻana i ke kino a me ka spatial (Gebbers & Adamchuk, 2010; Gevaert et al., 2015; Maes & Steppe, 2019). No kēia kumu, ʻo Agüera Vega et al. (2015) hoʻohana i kahi ʻōnaehana sensor multispectral i kau ʻia e UAV no ka loaʻa ʻana o nā kiʻi o kahi hua lā i ka wā ulu. Pēlā nō, ʻo Huang et al. (2009) e hoʻomaopopo i ka ʻike mamao ma muli o nā UAV hiki ke maʻalahi i ke ana ʻana o nā mea kanu a me ka lepo mai ka ʻikepili spectral i hōʻiliʻili ʻia. ʻO Verger et al. (2014) hoʻomohala a hoʻāʻo i kahi ʻenehana no ka helu ʻana i kahi huaʻōlelo ʻāpana ʻōmaʻomaʻo (GAI) mai nā ana hoʻohālikelike UAV i nā noi mahiʻai pololei, e kālele ana i ka palaoa a me nā mea kanu rapeseed. No laila, hāʻawi nā drones i nā mea hou no ka hoʻihoʻi ʻana i ka ʻike mokuʻāina me ka nānā pinepine ʻana a me ka hoʻonā spatial kiʻekiʻe (Dong et al., 2019; Garzonio et al., 2017; H. Zheng et al., 2016).
ʻO ka hui pū ʻana o nā puke koʻikoʻi ma nā drones mahiʻai.
Kahuʻula | Kumuhana ākea | E hoʻomaopopo ' |
1 | Nānā kaiapuni, ʻohi hooponopono, hooponopono weuweu | (Ad˜ ao et al., 2017; ʻO Agüera Vega et al., 2015; de Castro et al., 2018; Gomez-Cand ´ on ´ et al., 2014; Ua haʻi aku ʻo YB Huang et al., 2013; Khanal et al., 2017; Lopez-Granados, ´ 2011; Manfreda et al., 2018; P´ adua et al., 2017; Pena ˜ et al., 2013; Pʻerez-Ortiz et al., 2015; Rasmussen et al., 2013, 2016; Torres-S´ anchez et al., 2014; Torres-Sanchez, ´ Lopez-Granados, ´ & Pena, ˜ 2015; ʻO Verger et al., 2014; ʻO Von Bueren et al., 2015; C. Zhang & Kovacs, 2012) |
2 | phenotyping mamao, yield manaʻo, kumu hoʻohālike o ka ʻili, helu ʻana i nā mea kanu | (Bendig et al., 2013, 2014; Geipel et al., 2014; Gnadinger ¨ & Schmidhalter, 2017; Haghighattalab et al., 2016; Holman et al., 2016; Jin et al., 2017; W. Li et al., 2016; Maimaitijiang et al., 2017; Sankaran et al., 2015; Schirrmann et al., 2016; Shi et al., 2016; Yue et al., 2017; X. Zhou et al., 2017) |
3 | ʻO ke kiʻi wela no ka wai, kiʻi multispectral | (Baluja et al., 2012; Berni et al., 2009b; Berni et al., 2009a; Candiago et al., 2015; Gago et al., 2015; Gonzalez-Dugo et al., 2013, 2014; Grenzdorfer ¨ et al., 2008; ʻO Khaliq et al., 2019; Matese et al., 2015; Ribeiro-Gomes et al., 2017; Santesteban et al., 2017; Uto et al., 2013) |
4 | Kiʻi hypersectral, spectral kiʻi kiʻi | (Aasen et al., 2015a; Bareth et al., 2015; Hakala et al., 2013; Honkavaara et al., 2013a; ʻO Lucieer et al., 2014; Saari et al., 2011; Suomalainen et al., 2014) |
5 | Nā noi palapala 3D | (Jiʻenez-Brenes et al., 2017; Nex & Remondino, 2014; Salamí et al., 2014; Torres-S´ anchez, Lopez- ´ Granados, Serrano, et al., 2015; Zahawi et al., 2015; Zarco-Tejada et al., 2014) |
6 | Mākaʻikaʻi mahiʻai | (SR Herwitz et al., 2004; Hunt et al., 2010; CCD Lelong et al., 2008; Primicerio et al., 2012; Xiang & Tian, 2011) |
Eia kekahi, pono nā drones no nā hana paʻakikī i ka mahiʻai, me ka palapala ʻāina weed. ʻO nā kiʻi i paʻa ʻia e nā mea hana ua hōʻoia i ko lākou pono no ka ʻike mua ʻana i ka nahele ma nā kula (de Castro et al., 2018; Jimʻenez-Brenes et al., 2017; Lam et al., 2021; Lopez-Granados ´ et al., 2016; Rozenberg et al., 2021). Ma keia mea, de Castro et al. (2018) manaʻo ʻo ka hui ʻana o nā kiʻi UAV a me Object-Based Image Analysis (OBIA) i hiki ai i nā loea ke lanakila i ka pilikia o ka hoʻomaʻamaʻa ʻana i ka ʻike mua ʻana i nā hua mauʻu i ka wā mua, kahi hana nui i mua o ka noiʻi mauu. Likewise, Pena ˜ et al. (2013) hōʻike ʻo ka hoʻohana ʻana i nā kiʻi hoʻonā kiʻekiʻe kiʻekiʻe mai ka UAV me kahi kaʻina OBIA e hiki ai ke hoʻohua i nā palapala ʻāina mauʻu i nā mea kanu mua i hiki ke hoʻohana ʻia i ka hoʻolālā ʻana i ka hoʻokō ʻana i nā ana hoʻomalu mauu i ka wā. he hana ma waho aʻe o ka hiki o ka satellite a me nā kiʻi lele lele. Ke hoʻohālikelike ʻia i ka hoʻohālikelike ʻana i nā kiʻi a i ʻole nā algorithm ʻike mea, ʻoi aku ka maikaʻi o nā ʻenehana hoʻokaʻawale semantic i nā hana palapala weed (J. Deng et al., 2020), no laila e hiki ai i ka poʻe mahiʻai ke ʻike i nā kūlana kahua, hoʻēmi i nā poho, a hoʻomaikaʻi i nā hua i ka wā ulu (Ramesh. et al., 2020). Hiki ke hāʻawi i ke ana pololei o ka uhi o nā mea kanu mai nā kiʻi lewa kiʻekiʻe (Ramesh et al., 2020; A. Zheng et al., 2022). ʻOiai ko lākou hiki ke mamao
ʻO ka hoʻohālikelike ʻana i nā pika, nā ʻenehana hoʻokaʻawale semantic e koi i ka helu nui a me kahi hoʻomanaʻo GPU kiʻekiʻe (J. Deng et al., 2020).
Ma muli o ke aʻo ʻana o ka mīkini a me ka UAV, Pʻerez-Ortiz et al. (2015) manaʻo ʻia kahi ala palapala ʻāina weed e hoʻolako i nā hoʻolālā hoʻokele weeds i ka wā e hoʻohana ai ka poʻe mahiʻai i ka hoʻomalu ʻana i ka nahele ma hope o ka puka ʻana. ʻO ka mea hope loa, ʻo Rasmussen et al. (2013) i hōʻike ʻia e hāʻawi nā drones i ka ʻike maʻalahi me ka maʻalahi o ka hoʻonā spatial. Ma ke ʻano holoʻokoʻa, ʻo nā mea paʻi i loko o kēia puʻupuʻu e kālele ana i ka ʻimi ʻana i nā hiki o nā UAV e kākoʻo i ka ʻike mamao, ka nānā ʻana i nā mea kanu, a me ka palapala ʻāina weed. Pono ka noiʻi hohonu hou e noiʻi hou pehea e hiki ai i nā noi drone i ka nānā ʻana i ke kaiapuni, ka mālama ʻana i nā mea kanu, a me ka palapala ʻāina weed hiki ke hoʻokō i ka mahiʻai hoʻomau (Chamuah & Singh, 2019; Islam et al., 2021; Popescu et al., 2020; J . Su, Liu, et al., 2018) a hoʻoponopono i nā pilikia hoʻomalu o kēia ʻenehana i nā noi ʻinikua hua (Basnet & Bang, 2018; Chamuah & Singh, 2019, 2022; Meinen & Robinson, 2021). Pono nā mea noiʻi e noʻonoʻo i ka hōʻoia ʻana i nā ana i hōʻiliʻili ʻia e UAV me nā ʻenehana hana kūpono e hoʻomaikaʻi ai i ka maikaʻi loa o ka ʻikepili i hana ʻia (Manfreda et al., 2018). Eia kekahi, pono ka hoʻomohala ʻana i nā algorithms kūpono e ʻike ai i nā pika e hōʻike ana i nā nahele i nā kiʻi kikohoʻe a hoʻopau i ka ʻike pili ʻole i ka wā UAV weed mapping e pono ai (Gaˇsparovi'c et al., 2020; Hamylton et al., 2020; H. Huang et al. , 2018, 2020; Lopez- ´ Granados et al., 2016). ʻO ka noiʻi hou ʻana e pili ana i ka hoʻohana ʻana i nā ʻenehana hoʻokaʻawale semantic i ka ʻike ʻana i nā mea kanu, ka hoʻokaʻawale ʻana o ka lau, a me ka palapala ʻāina maʻi e ʻae ʻia (Fuentes-Pacheco et al., 2019; Kerkech et al., 2020).
Pūʻulu 2. ʻO nā paʻi ʻana o kēia pūʻulu i kālele ʻia i kekahi mau ʻano o nā drones mahiʻai. Pili i ka phenotyping mamao, Sankaran et al. (2015) nānā i ka hiki ke hoʻohana i ka haʻahaʻa haʻahaʻa, hoʻonā kiʻi kiʻi kiʻi lewa me nā UAV no ka phenotyping wikiwiki o nā mea kanu ma ke kula, a ke hoʻopaʻapaʻa nei lākou, ke hoʻohālikelike ʻia me nā kahua ʻike honua, ʻo nā UAV liʻiliʻi me nā mea ʻike kūpono e hāʻawi i nā pono he nui. , e like me ka maʻalahi o ke komo ʻana i ke kahua, ka ʻikepili hoʻonā kiʻekiʻe, ka ʻohi ʻikepili kūpono,
nā loiloi wikiwiki o nā kūlana ulu ulu, a me nā koina hana haʻahaʻa. Eia nō naʻe, ʻike nā mea kākau i ka hoʻohana pono ʻana o UAV no ke kahua phenotyping e hilinaʻi ana i ʻelua mau mea kumu, ʻo ia hoʻi, nā hiʻohiʻona UAV (e laʻa, palekana, kūpaʻa, kūlana, autonomy) a me nā hiʻohiʻona sensor (eg, hoʻonā, kaumaha, spectral wavelengths, field. o ka ike). Haghighattalab et al. (2016) i hoʻolālā i kahi pipeline hoʻoponopono kiʻi semi-aunoa e kiʻi i ka ʻikepili pae kiʻekiʻe mai nā kiʻi UAV a hoʻolalelale i ke kaʻina hana hānau. Holman et al. (2016) hoʻomohala i kahi kiʻekiʻe
throughput field phenotyping system and highlighted that UAV is hiki ke ohi i ka maikaʻi, voluminous, field-based phenotypic data, and that the device is effective for large areas a ma na wahi like ole.
No ka mea he mea koʻikoʻi loa ka ʻike ʻana i ka ʻike, ʻoiai ke loaʻa i ka manawa, hiki i nā UAV ke hāʻawi i nā ana āpau āpau a loaʻa maikaʻi ka ʻikepili kiʻekiʻe (Daakir et al., 2017; Demir et al., 2018). ; Enciso et al., 2019; Kulbacki et al., 2018; Pudelko et al., 2012). Ma kēia mea, ʻo Jin et al. (2017) ua hoʻohana i nā kiʻi kiʻi hoʻonā kiʻekiʻe i loaʻa e nā UAV ma nā wahi kiʻekiʻe haʻahaʻa e hoʻomohala a loiloi i kahi ala no ka helu ʻana i ka nui o nā mea kanu palaoa i ka wā e puka mai ai. Wahi a nā mea kākau, ua lanakila nā UAV i nā palena o nā ʻōnaehana rover i hoʻolako ʻia me nā kāmera a hōʻike i kahi ala non-invasive e hoʻohālikelike i ka nui o nā mea kanu i nā mea kanu, e ʻae ana i ka poʻe mahiʻai e hoʻokō i ka throughput kiʻekiʻe e pono ai no ke kahua phenotyping kūʻokoʻa i ka trafficability o ka lepo. Li et al. (2016) hōʻiliʻili i nā haneli kiʻi stereo me ka hoʻonā kiʻekiʻe loa me ka hoʻohana ʻana i kahi ʻōnaehana UAV e koho i nā ʻāpana maile, me ke kiʻekiʻe o ka canopy a me ka biomass ma luna o ka honua. ʻO ka hope, ʻo Yue et al. (2017) hiki ke hoʻonui i ke kiʻekiʻe o nā mea kanu i hoʻoholo ʻia mai nā UAV.
ʻO kahi ala e nānā ai i ka ulu ʻana o ka mea kanu, ʻo ia ka manaʻo o ka hoʻomohala ʻana i nā hiʻohiʻona o nā mea kanu (Bendig et al., 2014, 2015; Holman et al., 2016; Panday, Shrestha, et al., 2020; Sumesh et al., 2021). Ua hōʻike ʻia kekahi mau haʻawina i ka hiki ke kiʻi ʻia mai ka UAV e hopu i ke kiʻekiʻe o nā mea kanu a nānā i ko lākou ulu ʻana. Eia kekahi laʻana, Bendig et al. (2013) i wehewehe i ka hoʻomohala ʻana i nā ʻano hoʻohālike o ka ʻili o nā mea kanu me ka hoʻonā kiʻekiʻe loa ma lalo o 0.05 m me ka hoʻohana ʻana i ka UAV. Ua manaʻo lākou e ʻike i ka hua
ʻokoʻa o ka ulu ʻana a me kona hilinaʻi ʻana i ka mālama ʻana i nā mea kanu, cultivar, a me ke kaumaha. ʻO Bendig et al. (2014) hoʻohana i nā UAV e koho i ka biomass hou a maloʻo e pili ana i ke kiʻekiʻe o nā mea kanu i unuhi ʻia mai nā hiʻohiʻona o nā mea kanu a ʻike ʻia, ʻaʻole like me nā lewa a me ka nānā ʻana i ka laser terrestrial, hiki i nā kiʻi hoʻonā kiʻekiʻe mai nā UAV ke hoʻonui nui i ka pololei o ke kiʻekiʻe o nā mea kanu no ka ulu ʻokoʻa. nā pae. Ma ke ano like, Geipel et al. (2014) hoʻohana i nā UAV i kā lākou noiʻi e kiʻi i nā kiʻi
ʻO ka hui ʻana o ka spectral a me ka spatial modeling e pili ana i nā kiʻi lewa a me nā ʻano hoʻohālike o ka mea kanu he ala kūpono ia no ka wānana ʻana i ka hua mai ka waena o ke kau. ʻO ka hope, ua nānā ʻo Gnadinger ¨ a me Schmidhalter (2017) i ka pono o ka UAV i ka phenotyping precision a hōʻike i ka hoʻohana ʻana i kēia ʻenehana hiki ke hoʻonui i ka hoʻokele mahiʻai a hiki i ka hoʻokolohua kahua no ka hoʻoulu ʻana a me nā kumu agronomic. Ma ke ʻano holoʻokoʻa, ʻike mākou i ka nānā ʻana o nā paʻi i ka cluster 2 i nā pono nui o nā UAV ma kahi mamao.
ka phenotyping, ka hoʻohua ʻana, ka hoʻolikelike ʻana o ka ʻili, a me ka helu mea kanu. Hiki i nā haʻawina i ka wā e hiki mai ana ke eli hohonu ma o ka hoʻomohala ʻana i nā ʻano hou no ka phenotyping mamao e hiki ke hoʻokaʻawale a hoʻopaʻa pono i ka hana ʻana o ka ʻikepili i ʻike mamao (Barabaschi et al., 2016; Liebisch et al., 2015; Mochida et al., 2015; S. Zhou et al. ., 2021). Eia kekahi, pono e noiʻi ʻia ka hana o nā mea ʻike IoT i kau ʻia ma luna o nā UAV a me ke kālepa ʻana ma waena o kā lākou mau koina, hana, a me ka pololei o ka hoʻohālikelike ʻana.
e hiki mai ana (Ju & Son, 2018a, 2018b; Xie & Yang, 2020; Yue et al., 2018). ʻO ka mea hope loa, pono e hoʻomohala i nā ʻano hana hoʻoili kiʻi kūpono e hiki ai ke hoʻopuka i ka ʻike hilinaʻi, e hoʻonui i ka pono i ka hana mahiʻai, a e hōʻemi i ka hana helu manual a nā mahiʻai (RU Khan et al., 2021; Koh et al., 2021; Lin & Guo, 2020; C. Zhang et al., 2020).
Hui 3. Kūkākūkā nā mea paʻi i loko o kēia pūʻulu i nā ʻano ʻōnaehana kiʻi like ʻole no ka ʻike mamao o nā kumuwaiwai mahiʻai i hoʻohana ʻia ma nā kahua UAV. Ma kēiaʻano, hiki i ke kiʻi kiʻi wela ke nānā i nā mahana wela e pale i ka pōʻino o nā mea kanu aʻike i ke kaumaha o ka maloʻo ma mua (Awais et al., 2022; García-Tejero et al., 2018; Sankaran et al., 2015; Santesteban et al., 2017; Yeom, 2021). ʻO Baluja et al. (2012) ua ʻōlelo ʻo ka hoʻohana ʻana i nā kāmera multispectral a me ka wela ma luna o ka
Ua hiki i nā mea noiʻi ke kiʻi i nā kiʻi hoʻonā kiʻekiʻe a nānā i ke kūlana wai waina. He mea pono paha kēia no ka hoʻomohala ʻana i nā hiʻohiʻona hoʻonohonoho wai hou me ka hoʻohana ʻana i ka ʻikepili mamao-sensing (Baluja et al., 2012). Ma muli o ka
ka palena haawe o UAV, Ribeiro-Gomes et al. (2017) noʻonoʻo i ka hoʻohui ʻana o nā kiʻi kiʻi wela ʻole i loko o ka UAVS no ka hoʻoholo ʻana i ke koʻikoʻi o ka wai i loko o nā mea kanu, ʻo ia ka mea e ʻoi aku ka maikaʻi o kēia ʻano UAV ma mua o ka ʻike mamao ma muli o ka satellite a me nā UAV i hoʻolako ʻia me nā kiʻi kamepiula wela. Wahi a nā mea kākau, ʻoi aku ka māmā o nā kāmeʻa wela uncooled ma mua o nā kāmela i hoʻoluʻu, e koi ana i ka calibration kūpono. Gonzalez-Dugo et al. (2014) hōʻike i ka hoʻohua maikaʻi ʻana o nā kiʻi wela i nā palapala spatial o nā hōʻailona koʻikoʻi o ka wai no ka loiloi ʻana i ke kūlana wai a me ka helu ʻana i ke koʻikoʻi o ka wai ma waena a ma loko o nā māla hua citrus. Gonzalez-Dugo et al. (2013) a me Santesteban et al. (2017) i noiʻi i ka hoʻohana ʻana i nā kiʻi wela UAV hoʻonā kiʻekiʻe e hoʻohālikelike i ke ʻano o ke kūlana wai o kahi māla pāʻoihana a me kahi māla waina.
Hiki i ke kiʻi multispectral ke hāʻawi i ka ʻikepili nui i ka hoʻohālikelike ʻana me nā kiʻi RGB (Red, Green, a me Blue) kuʻuna (Ad˜ ao et al., 2017; Navia et al., 2016). Hiki i kēia ʻikepili spectral, me ka ʻikepili spatial, ke kōkua i ka hoʻokaʻawale ʻana, ka palapala ʻāina, ka wānana, ka wānana, a me nā kumu ʻike (Berni et al., 2009b). Wahi a Candiago et al. (2015), hiki i ka UAV-based multispectral imaging ke hāʻawi nui i ka loiloi huaʻai a me ka mahiʻai pololei ma ke ʻano he kumu hilinaʻi a maikaʻi. Eia kekahi,
ʻO Khaliq et al. (2019) i hoʻohālikelike ma waena o ka satellite a me ka UAVbased multispectral imaging. ʻO nā kiʻi i hoʻokumu ʻia i ka UAV ua ʻoi aku ka pololei o ka wehewehe ʻana i ka ʻokoʻa o ka māla waina a me nā palapala ʻāina ikaika no ka hōʻike ʻana i nā canopies. Ma kahi pōkole, kūkākūkā nā ʻatikala o kēia puʻupuʻu i ka hoʻopili ʻana o nā mea ʻike kiʻi wela a me nā ʻano multispectral i loko o nā UAV mahiʻai. No laila, pono ka noiʻi hou aʻe e hoʻomaopopo i ka hiki ke hoʻohui ʻia ke kiʻi thermal a me multispectral me AI
ʻenehana (e laʻa, ke aʻo hohonu) e ʻike i ke koʻikoʻi o nā mea kanu (Ampatzidis et al., 2020; Ampatzidis & Partel, 2019; Jung et al., 2021; Santesteban et al., 2017; Syeda et al., 2021). E kōkua ia mau ʻike e hōʻoia i ka ʻike ʻoi aku ka maikaʻi a me ka pololei a me ka nānā ʻana i ka ulu ʻana o ka mea kanu, ke kaumaha, a me ka phenology (Buters et al., 2019; Cao et al., 2020; Neupane & BaysalGurel, 2021; L. Zhou et al., 2020).
Pūʻulu 4. Aia kēia pūʻulu he ʻehiku mau pepa e pili ana i ke kuleana koʻikoʻi o ke kiʻi spectral a me ka hyperspectral imaging i ke kākoʻo ʻana i nā hana mahiʻai. Ua hoʻokumuʻo Hyperspectral imaging iā ia iho ma keʻano heʻanoʻike mamao e hiki ai i ka loiloi nui o ka'ōnaehana honua (Schaepman et al., 2009) . ka hāʻawi ʻana i nā ʻāpana o ka ʻili
i loko o nā pika i hui pū ʻia (Kirsch et al., 2018; Zhao et al., 2022). ʻO ia hoʻi, ʻo ka hoʻonā hiʻohiʻona kiʻekiʻe i hāʻawi ʻia e nā ʻōnaehana hyperspectral e hiki ai ke koho pololei ʻana i nā ʻāpana like ʻole, e like me nā waiwai meaʻai a i ʻole ka wai lau lau (Suomalainen et al., 2014). Ua noiʻi nā mea noiʻi ma kēia pūʻulu i nā ʻano like ʻole o ia ʻōnaehana. Ma waena o nā mea ʻē aʻe, ʻo Aasen et al. (2015b) hāʻawi i kahi ala kūʻokoʻa no ka loaʻa ʻana o ka ʻike hyperspectral ʻekolu-dimensional mai ka māmā
nā kiʻi paʻi kiʻi i hoʻohana ʻia ma nā UAV no ka nānā ʻana i nā mea kanu. ʻO Lucieer et al. (2014) kūkākūkā i ka hoʻolālā, hoʻomohala ʻana, a me nā hana ea o kahi novel hyperspectral UAS a me ka calibration, ka nānā ʻana, a me ka wehewehe ʻana i ka ʻikepili kiʻi i hōʻiliʻili ʻia me ia. ʻO ka hope, ʻo Honkavaara et al. (2013b) hoʻomohala i kahi ala hoʻoponopono piha no FabryPerot interferometer-based spectral kiʻi a hōʻike i kona hoʻohana ʻana i kahi kaʻina hana koho biomass no ka mahiʻai pololei. ʻO nā ala e hiki mai ana no kēia puʻupuʻu o kēia manawa e pili ana i ka pono o ka hoʻomaikaʻi ʻana i ka ʻenehana i nā ʻenehana sensor (Aasen et al., 2015b) a me ka pono no ka hoʻohui ʻana a me ka hoʻonui ʻana i nā ʻenehana hoʻohui, ʻo ia hoʻi ka ʻikepili nui a me nā analytics (Ang & Seng, 2021; Radoglou -Grammatikis et al., 2020; Shakoor et al., 2019). ʻO ka mea hope ke kumu nui mai ka ʻikepili ulu mau i hana ʻia e nā mea ʻike like ʻole i hoʻokō ʻia i ka mahiʻai akamai (C. Li & Niu, 2020; A. Rejeb et al., 2022; Y. Su & Wang, 2021).
Cluster 5. Ua nānā nā puke i loko o kēia pūʻulu i nā noi 3Dmapping e pili ana i nā drones. ʻO ka hoʻohana ʻana i nā drones no ka palapala palapala 3D hiki ke hoʻohaʻahaʻa i ka hana paʻakikī a hoʻonui i ka pono (Torres-Sanchez ´ et al., 2015). ʻO nā ʻatikala ʻelima i loko o ka puʻupuʻu i kālele nui ʻia i nā noi nānā mea kanu. No ka laʻana, no ka loaʻa ʻana o nā ʻikepili ʻekolu e pili ana i ka ʻāpana canopy, ke kiʻekiʻe o ka lāʻau, a me ka leo lei aliʻi, Torres-Sanchez ´ et al. (2015) hoʻohana i ka ʻenehana UAV no ka hoʻohua ʻana i nā hiʻohiʻona ʻili kikohoʻe a laila e hoʻokokoke ana i ka nānā ʻana kiʻi ma muli o nā mea (OBIA). Eia kekahi, ʻo Zarco-Tejada et al. (2014) i helu ʻia ke kiʻekiʻe o ka lāʻau ma o ka hoʻohui ʻana i ka ʻenehana UAV a me nā ʻano hana hou kiʻi kiʻi ʻekolu. ʻO Jimʻenez-Brenes Lopez-Granados, ʻo De Castro, et al. (2017) hōʻike i kahi kaʻina hana hou no ka nānā ʻana i nā manawa he nui, 3D o ka nui o nā kumulāʻau ʻoliva ma o ka hoʻohui ʻana i ka ʻenehana UAV me ke ʻano OBIA kiʻekiʻe. ʻO nā ala hoihoi no nā hana e hiki mai ana i loko o kēia pūʻulu ʻo ia ka hoʻomaikaʻi ʻana i kēia manawa
methodologies (Zarco-Tejada et al., 2014) no nā kumu hoʻohālike kikohoʻe honua (Ajayi et al., 2017; Jaud et al., 2016), e like me OBIA (de Castro et al., 2018, 2020; Ventura et al. , 2018), a me ke kūkulu hou ʻana i ke kiʻi a i ʻole ka hoʻomohala ʻana i nā ʻano hana hou (Díaz-Varela et al., 2015; Torres-S' anchez et al., 2015).
Cluster 6. Kūkākūkā kēia pūʻulu i ke kuleana o nā drones i ka nānā ʻana i ka mahiʻai. Hiki i nā UAV ke hoʻokō a lanakila i nā hemahema o ka satellite a me nā kiʻi mokulele. Eia kekahi laʻana, hiki iā lākou ke hāʻawi i ka hoʻonā kiʻekiʻe kokoke i ka manawa maoli me ka liʻiliʻi o ka wahie a i ʻole nā pilikia hoʻokele, ka hopena i ka nānā mau a me ka manawa maoli a me ka hoʻomaikaʻi ʻana i ka hoʻoholo ʻana (S. Herwitz et al., 2004). ʻO kekahi kōkua koʻikoʻi o nā UAV ʻo ko lākou hiki ke hāʻawi i ka ʻikepili kikoʻī pūnaewele no ka mahiʻai pololei a i ʻole ka mahiʻai kikoʻī kikoʻī e like me kā lākou hoʻonā kiʻekiʻe, nā ʻikepili kikoʻī e pili ana i nā ʻāpana like ʻole e hiki ai i ka poʻe mahiʻai ke hoʻokaʻawale i ka ʻāina i nā ʻāpana homogeneous a mālama iā lākou e like me ia (Hunt et al. , 2010; CC Lelong et al., 2008; Primicerio et al., 2012). Hiki ke kākoʻo i ka nānā ʻana i ka mahiʻai e pili ana i ka UAV i ka nānā ʻana i ka palekana meaʻai a me ka hoʻoholo ʻana (SR Herwitz et al., 2004). No ka holomua ʻana i ka noiʻi ʻana i ka nānā ʻana i ka mahiʻai, ʻaʻole wale ka hoʻomaikaʻi ʻana i nā sensor, UAV, a me nā ʻenehana pili ʻē aʻe a me kā lākou kamaʻilio a me nā ʻano hoʻoili data e pono ai (Ewing et al., 2020; Shuai et al., 2019), akā hoʻohui pū i nā drones me nā ʻano like ʻole. ʻenehana no ka hoʻonui ʻana i nā hana like ʻole e pili ana i ka mahiʻai akamai, e like me ka nānā ʻana, ka nānā ʻana i ka mahiʻai, a me ka hoʻoholo ʻana, he wahi noiʻi kiʻekiʻe loa ia (Alsamhi et al., 2021; Popescu et al., 2020; Vuran et al., 2018). Ma kēia ʻano, hāʻawi ʻo IoT, WSN, a me ka ʻikepili nui i nā mana hoʻohui hoihoi (van der Merwe et al., 2020). ʻO nā kumukūʻai hoʻokō, ka mālama ʻana i ke kumukūʻai, ka ikaika o ka ikehu, a me ka palekana ʻikepili i waena o nā wahi i noiʻi ʻia no ia hoʻohui (Masroor et al., 2021).
Nā ʻāina a me nā kula hoʻonaʻauao
ʻO ka ʻanuʻu hope loa, ʻo ia ka hoʻokolokolo ʻana i ka ʻāina i hānau ʻia ai a me nā pilina hoʻonaʻauao o nā mea kākau. Ma o kēia hoʻopaʻa ʻana, manaʻo mākou e hoʻomaopopo maikaʻi i ka māhele ʻāina o nā loea i hāʻawi i nā noi o nā drones i ka mahiʻai. He mea nui ka ʻike ʻana i ka ʻokoʻa o nā ʻāina a me nā ʻoihana kula. Mai kahi hiʻohiʻona ʻāina, ʻo ʻAmelika, Kina, India, a me Italia ke kūlana ma luna o ka papa inoa e pili ana i ka nui o nā paʻi (Papa 7). ʻO kēia manawa
ʻO ka noiʻi ʻana i nā drones mahiʻai ka mea nui i waena o ʻAmelika ʻAmelika a me ʻAsia, ʻo ka mea nui ma muli o kā lākou hana kiʻekiʻe i nā noi mahiʻai pololei. No ka laʻana, ma USA, ua manaʻo ʻia ka mākeke o nā drones mahiʻai ma 841.9 miliona USD i ka makahiki 2020, e helu ana ma kahi o 30% o ka māhele mākeke honua (ReportLinker, 2021). Ke kūlana nei ʻo ia ka ʻoihana waiwai nui loa o ka honua, ua wānana ʻia ʻo Kina e hōʻea i ka nui o ka mākeke o 2.6 biliona USD i ka makahiki 2027. Ke noi nei kēia ʻāina i nā drones mahiʻai e lanakila i nā pilikia huahana a loaʻa i nā hua ʻoi aku ka maikaʻi, ka hoʻohaʻahaʻa hana, a me nā mea hoʻokomo liʻiliʻi. Eia nō naʻe, ʻo ka hoʻohana ʻana i ka ʻenehana ma Kina e alakaʻi ʻia e nā mea e like me ka nui o ka heluna kanaka a me ka pono e hoʻomaikaʻi a hoʻomaikaʻi i nā hana hoʻokele waiwai.
ʻO nā ʻāina kiʻekiʻe loa a me nā kulanui/hui e hāʻawi nei
noiʻi pili drone mahiʻai.
Rank | 'āina |
1 | USA |
2 | China |
3 | ʻInia |
4 | Ikalia |
5 | Kepania |
6 | Kelemānia |
7 | Palakila |
8 | Nuhōlani |
9 | Iapana |
10 | Aupuni Mōʻī Hui Pū ʻia |
Rank | Kula Nui/ Hui |
1 | Ke Kula Nui ʻepekema Kina |
2 | Ke Kuhina Mahiai o ka Lepupalika Kanaka o Kina |
3 | Ka ʻaha kūkā kiʻekiʻe o nā noiʻi ʻepekema |
4 | Ke Kulanui ʻo A&M Texas |
5 | Kula Hanāʻo Kina |
6 | Ke lawelawe noiʻi mahiʻai USDA |
7 | CSIC - Instituto de Agricultura Sostenible IAS |
8 | Kula Purdue |
9 | 'Aha 'Imi Imi Lahui |
10 | Ke Kulanui ʻAmelika Hema |
Mai ke kulanui a me ka hoʻonohonoho ʻana, ʻo ka Chinese Academy of Sciences ke poʻo i ka papa inoa e pili ana i ka helu o nā paʻi, a ukali ʻia e ka Ministry of Agriculture of the People's Republic of China a me Consejo Superior de Investigaciones Científicas. Ua pani ʻia ʻo Chinese Academy of Science e nā mea kākau ʻo Liao Xiaohan lāua ʻo Li Jun; 'O Han Wenting ka 'Oihana Mahiai o ka Lepupalika Kanaka o Kina; a ʻo Consejo Superior de Investigaciones Científicas e pani ʻia e Lopez-Granados, ´ F. a me Pena, ˜ Jos´e María S. Mai USA mai, ʻike nā kulanui e like me Texas A&M University a me Purdue University i kā lākou
haʻiʻōlelo. Hōʻike ʻia nā kulanui me ka helu kiʻekiʻe loa o nā paʻi a me ko lākou pili i ka Fig. .
Loaʻa i kā mākou koho ʻana i nā puke pai like ʻole, e hoʻopili ana i nā ʻikepili āpau i loaʻa. E like me ka mea i hōʻike ʻia ma ka Papa 8, ʻo Remote Sensing me 258 mau ʻatikala ma luna, a ukali ʻia e Journal of Intelligent and Robotic Systems: Theory and Applications me 126 a me Computers and Electronics in Agriculture me 98 mau ʻatikala. ʻOiai ʻo Remote Sensing ka nui o ka nānā ʻana i ka noi a me ka hoʻomohala ʻana i nā drones, ʻo Computers a me Electronics in Agriculture ka mea e uhi nui i ka holomua o ka lako kamepiula, lako polokalamu, uila, a me nā ʻōnaehana hoʻomalu i ka mahiʻai. ʻO nā puka kea, e like me IEEE Robotics a me Automation Letters me 87 paʻi a me IEEE Access me 34 paʻi, ʻo ia hoʻi nā hale kūʻai mua ma ke kula. Ua hāʻawi ka poʻe kiʻekiʻe he ʻumikūmālima i nā palapala me 959 mau palapala, ʻo ia ka 20.40% o nā paʻi a pau. Hiki iā mākou ke nānā i ke koʻikoʻi a me ka like ma waena o nā puke pai puke. ʻO ka hōʻuluʻulu ʻana o ka co-citation e hāʻawi i ʻekolu mau puʻupuʻu, e like me ka mea i hōʻike ʻia ma ka Fig.
a me ka International Journal of Remote Sensing. ʻO kēia mau puka waho a pau he mau puke moʻolelo kaulana loa ma nā wahi o ka ʻike mamao a me ka mahiʻai pololei. Aia ka pūʻulu ʻōmaʻomaʻo i nā puke pai e pili ana i nā robotics, e like me Journal of Intelligent and Robotic Systems: Theory and Applications, IEEE Robotics and Automation Letters, IEEE Access, a me Drones. Hoʻopuka ka hapa nui o kēia mau puka i nā pepa ma ka automation a pono no nā ʻenekini mahiʻai. Hoʻokumu ʻia ka hui hope e nā puke pai e pili ana i ka agronomy a me ka ʻenekinia mahiʻai, e like me Agronomy a me International Journal of Agricultural and Biological Engineering.
Nā puke pai 15 kiʻekiʻe ma ka noiʻi pili drone pili.
Rank | Pai | Helu |
1 | Kamaʻāina mamao | 258 |
2 | Nūpepa no nā Pūnaehana Naʻauao a me Robotic: Theory and noi | 126 |
3 | Kamepiula a me Electronics ma ka Mahiai | 98 |
4 | IEEE Robotics and Automation Letters | 87 |
5 | nā mea e loaʻa ka mea nalo | 73 |
6 | Ka Nupepa International of Remote Sensing | 42 |
7 | Mahiai Kūpono | 41 |
8 | Drones | 40 |
9 | Kūkino | 34 |
10 | Loaʻa iā IEEE | 34 |
11 | Nupepa International o Advanced Robotic Systems | 31 |
12 | Ka Nupepa International of Agricultural and Biological Engineering | 25 |
13 | PLOS ONE | 25 |
14 | Nūpepa o Field Robotics | 23 |
15 | Biosystems Engineering | 23 |
Panina
hōʻuluʻulu manaʻo
Ma kēia haʻawina, hōʻuluʻulu mākou a nānā i ka noiʻi e pili ana i nā drones mahiʻai. Ke hoʻohana nei i nā ʻenehana bibliometric like ʻole, ua hoʻoikaika mākou e loaʻa ka ʻike maikaʻi aʻe o ke ʻano noʻonoʻo o ka noiʻi pili drone pili i ka mahiʻai. Ma ka hōʻuluʻulu ʻana, hāʻawi kā mākou loiloi i kekahi mau haʻawina ma ka ʻike ʻana a me ke kūkākūkā ʻana i nā huaʻōlelo i loko o ka palapala, e hōʻike ana i nā pūʻulu ʻike i ka wā e hoʻokumu ana i nā kaiāulu like semantically i ke kahua o nā drones, e wehewehe ana i ka noiʻi mua, a me ka ʻōlelo ʻana i nā kuhikuhi noiʻi e hiki mai ana. Ma lalo nei mākou e wehewehe i nā ʻike nui o ka loiloi e pili ana i ka hoʻomohala ʻana i nā drones mahiʻai:
• Ua ulu wikiwiki nā palapala holoʻokoʻa a ua huki nui ʻia i nā makahiki he ʻumi i hala, e like me ka mea i hōʻike ʻia e ka piʻi ʻana o ka helu o nā ʻatikala ma hope o 2012. ʻOiai ʻaʻole i loaʻa i kēia kahua ʻike i kona oʻo piha (Barrientos et al., 2011; Maes. & Steppe, 2019), ʻaʻole i pane ʻia kekahi mau nīnau. No ka laʻana, wehe ʻia ka pono o nā drones i ka mahiʻai i loko no ka hoʻopaʻapaʻa (Aslan et al., 2022; Krul et al., 2021; Rold'an et al., 2015). ʻO ka paʻakikī o nā hiʻohiʻona kula a me nā kūlana kiʻi like ʻole (e laʻa, nā aka a me ka hoʻomālamalama) hiki ke hopena i kahi ʻokoʻa kiʻekiʻe o ka papa kiʻekiʻe (Yao et al., 2019). ʻOiai i nā pae noiʻi hope loa, ua hoʻokūkū ʻia nā mea noiʻi e hoʻoholo i nā hoʻolālā lele maikaʻi loa e like me nā hiʻohiʻona kūikawā a me ka maikaʻi o ke kiʻi pono (Soares et al., 2021; Tu et al.,
2020).
• ʻIke mākou ua holomua ka māla mai ka hoʻomohala ʻana i nā ʻōnaehana UAV maikaʻi i ka hoʻokomo ʻana i nā ʻenehana AI, e like me ke aʻo ʻana i ka mīkini a me ka aʻo hohonu i ka hoʻolālā ʻana o nā drones mahiʻai (Bah et al., 2018; Kitano et al., 2019; Maimaitijiang et al. , 2020; Mazzia et al., 2020; Tetila et al., 2020).
• Ua kūkākūkā nui ka noiʻi ʻana i nā drones mahiʻai no ka ʻike mamao ma o ka ʻimi ʻana i nā mea hiki o ka ʻenehana i ka nānā ʻana i ke kaiapuni, ka mālama ʻana i nā mea kanu, a me ka mālama ʻana i ka mauʻu (cluster 1) a me ka phenotyping mamao a me ka helu hua (cluster 2). ʻO kahi pūʻulu o nā haʻawina koʻikoʻi e pili ana i nā drones mahiʻai ʻo Austin (2010), Berni et al. (2009)a, Herwitz et al. (2004), Nex a me Remondino (2014), a me Zhang a me Kovacs (2012). Ua hoʻomohala kēia mau haʻawina i ke kumu noʻonoʻo o ka noiʻi pili drone i ka pōʻaiapili o ka mahiʻai.
• E pili ana i ke kaʻina hana, ua ʻike mākou ʻo ka hapa nui o ka noiʻi i hana ʻia i kēia manawa ua haku ʻia me ka hoʻolālā ʻōnaehana, ka manaʻo, a i ʻole ka loiloi loiloi (Inoue, 2020; Nex & Remondino, 2014; Pʻerez-Ortiz et al. , 2015; Yao et al., 2019). ʻIke pū mākou i ka nele o nā ʻano empirical, qualitative, a me ka hihia-study-based ma ka hana i ka noiʻi ʻana i nā drones mahiʻai.
• I kēia mau lā, ua huki nui ʻia nā kumuhana e pili ana i ka mahiʻai pololei, nā ʻenehana AI, nā mea kanu pono, a me ka loiloi wai (Espinoza et al., 2017; Gomez-Cand ´ on ´ et al., 2016; Matese et al., 2015; Matese & Di Gennaro, 2018, 2021; Z. Zhou et al., 2021). ʻO ka nānā pono ʻana i nā pūʻulu noiʻi i ʻelua mau manawa ʻokoʻa, 1990–2010 a me 2011–2021, hōʻike i ka holomua o ka hoʻolālā naʻauao o ka domain. ʻO ka manawa mai 1990 a hiki i 2010 ke kūkulu ʻana i nā manaʻo kikowaena a me nā manaʻo o nā drones, i ʻike ʻia mai ke kūkākūkā ʻana o ka hoʻolālā UAV, hoʻomohala, a me ka hoʻokō. I ka lua o ka manawa, hoʻonui ka manaʻo noiʻi i nā haʻawina mua, e hoʻoikaika ana e synthesize i nā hihia hoʻohana UAV i ka mahiʻai. Ua ʻike pū mākou i nā noiʻi he nui e kūkākūkā ana i nā noi drone i nā hana kiʻi kiʻi a me ka mahiʻai pololei.
Rank | Pai | Helu |
1 | Kamaʻāina mamao | 258 |
2 | Nūpepa no nā Pūnaehana Naʻauao a me Robotic: Theory and | 126 |
noi | ||
3 | Kamepiula a me Electronics ma ka Mahiai | 98 |
4 | IEEE Robotics and Automation Letters | 87 |
5 | nā mea e loaʻa ka mea nalo | 73 |
6 | Ka Nupepa International of Remote Sensing | 42 |
7 | Mahiai Kūpono | 41 |
8 | Drones | 40 |
9 | Kūkino | 34 |
10 | Loaʻa iā IEEE | 34 |
11 | Nupepa International o Advanced Robotic Systems | 31 |
12 | Ka Nupepa International of Agricultural and Biological Engineering | 25 |
13 | PLOS ONE | 25 |
14 | Nūpepa o Field Robotics | 23 |
15 | Biosystems Engineering | 22 |
mea hoʻomaoe
Ua hoʻolālā ʻia kā mākou loiloi bibliometric me ka poʻe loea, nā mahiʻai, nā loea mahiʻai, nā ʻōlelo aʻoaʻo hua, a me nā mea hoʻolālā ʻōnaehana UAV. I ka ʻike maikaʻi o ka poʻe kākau, ʻo ia kekahi o nā loiloi kumu mua i hana i kahi loiloi bibliometric hohonu o
nā noi drone ma ka mahiʻai. Ua alakaʻi mākou i kahi loiloi piha o kēia hui ʻike, me ka hoʻohana ʻana i ka ʻōlelo a me nā loiloi co-citation o nā puke. ʻO kā mākou ho'āʻo e wehewehe i ke ʻano noʻonoʻo o ka noiʻi drone hāʻawi pū kekahi i nā ʻike hou no ka poʻe hoʻonaʻauao. ʻO ka nānā pono ʻana i nā huaʻōlelo i hoʻohana ʻia i ka wā e hōʻike ana i nā wahi wela a me nā wahi noiʻi kikoʻī i loko o nā palapala pili drone. Eia kekahi, ke hōʻike nei mākou i kahi papa inoa o nā haʻawina i haʻi ʻia e ʻike i nā hana noiʻi koʻikoʻi i hoʻopau ʻia ma ke kula. ʻO ka ʻike ʻana i nā ʻatikala a me nā huaʻōlelo e hiki ke hāʻawi i kahi kumu hoʻomaka paʻa e wehe i kekahi mau ala no nā haʻawina e hiki mai ana.
ʻO ka mea nui, ua hōʻike mākou i nā pūʻulu e hoʻokaʻawale i nā hana like a wehewehe i nā hopena. ʻO nā haʻawina i hoʻokaʻawale ʻia i loko o nā puʻupuʻu kōkua i ka hoʻomaopopo ʻana i ke ʻano o ka naʻauao o ka noiʻi UAV. ʻO ka mea nui, ua ʻike mākou i kahi pōloli o nā noiʻi e noiʻi ana i nā kumu hoʻohana drones
a me nā pale i nā hana mahiʻai (e nānā i ka Papa 9). Hiki i nā mea noiʻi i ka wā e hiki mai ana ke hoʻoponopono i kēia āpau ma o ka hoʻokō ʻana i nā noiʻi empirical e loiloi i nā kumu hoʻohana drones i nā hana mahiʻai like ʻole a me nā kūlana climatic. Eia kekahi, pono e kākoʻo ʻia ka noiʻi noiʻi e pili ana i ka pono o nā drones me ka ʻikepili maoli mai ke kula. Eia kekahi, ʻoi aku ka maikaʻi o ka hoʻopili ʻana i ka poʻe mahiʻai a me nā luna i ka noiʻi hoʻonaʻauao no ka holomua theoretical a me ka holomua o ka noiʻi drone. Ua hiki nō iā mākou ke ʻike i nā mea noiʻi koʻikoʻi a me kā lākou mau haʻawina, he mea nui ia no ka mea hiki i ka ʻike i nā hana seminal hou ke hāʻawi i kahi alakaʻi no nā hana hoʻonaʻauao e hiki mai ana.
9 Pūnaewele
Nā pale hoʻokomo UAV.
Ka pale | Description |
Ka mālamaʻikepili | He paʻakikī nui ka palekana Cyber no ka hoʻokō Nā hoʻonā IoT (Masroor et al., 2021). |
Interoperability a hoʻohui ' | ʻO nā ʻenehana like ʻole e like me UAV, WSN, IoT, etc. pono e hoʻohui a hoʻouna i ka ʻikepili i hoʻonui i ka pae paʻakikī (Alsamhi et al., 2021; Popescu et al., 2020; Vuran et al., 2018). |
Nā koina hoʻokō | ʻO kēia ka hihia no nā mahiʻai liʻiliʻi a no ka hoʻohui ʻana i nā ʻenehana ʻokiʻoki like ʻole ( Masroor et al., 2021). |
ʻIke hana a ʻike | Pono nā hoʻokele drone akamai e hana i nā UAV. Eia kekahi, ka hoʻokō ʻana i nā ʻoki ʻoki like ʻole Pono nā ʻenehana i nā limahana akamai (YB Huang et al., 2013; Tsouros et al., 2019). |
Enekinia Mana a lele lōʻihi | ʻAʻole hiki ke hoʻohana ʻia nā drones no nā hola lōʻihi a me ka uhi nā wahi nui (Hardin & Hardin, 2010; Laliberte et al., 2007). |
Paʻa, hilinaʻi, a hiki ke hana | ʻAʻole paʻa nā drones i ka wā ʻino (Hardin & Hardin, 2010; Laliberte et al., 2007). |
Uku kau palena a ka maikaʻi o nā naʻau | Hiki i nā Drones ke lawe i nā ukana liʻiliʻi hiki ke hoʻouka i nā mea ʻike haʻahaʻa haʻahaʻa (Nebiker et al., 2008). |
hooponopono | No ka mea hiki ke pilikia nā drones, aia nā mea koʻikoʻi nā hoʻoponopono ma kekahi mau wahi (Hardin & Jensen, 2011; Laliberte & Rango, 2011). |
Ka ike o ka poe mahiai a hoihoi | E like me nā ʻenehana ʻokiʻoki ʻē aʻe, nā drones ' pono ka hoʻokō kūleʻa i ka ʻike a me kekahi hele pū me ka maopopo ʻole (Fisher et al., 2009; Lambert et al., 2004; Stafford, 2000). |
Ma muli o ka pono mau e hoʻohana pono i nā kumuwaiwai i loaʻa e hoʻonui i nā hua, hiki i ka poʻe mahiʻai ke hoʻohana pono i nā drones e hōʻoia i ka wikiwiki, pololei, a me ka uku kūpono o kā lākou mau māla. Hiki i ka ʻenehana ke kākoʻo i ka poʻe mahiʻai e hoʻoholo i ke ʻano o kā lākou mea kanu a nānā i ke kūlana wai, ke ʻano o ka oʻo ʻana, ka ʻai ʻana o nā pepeke, a me nā pono meaʻai. Hiki i nā mana mamao o nā drones ke hāʻawi i ka poʻe mahiʻai i ka ʻikepili koʻikoʻi e kali i nā pilikia i ka wā mua a hana koke i nā hana kūpono. Eia naʻe, hiki ke ʻike ʻia nā pōmaikaʻi o ka ʻenehana inā e hoʻoponopono pono ʻia nā pilikia. Ma ka malamalama o ka
nā pilikia o kēia manawa e pili ana i ka palekana ʻikepili, nā pilikia ʻenehana sensor (e like me ka hilinaʻi a i ʻole ka pololei o nā ana), paʻakikī o ka hoʻohui ʻana, a me nā kumukūʻai hoʻokō nui, pono nā noiʻi e hiki mai ana e nānā i ka ʻenehana, hoʻokele waiwai, a me ka hiki ke hana o ka hoʻohui ʻana i nā drones mahiʻai a me nā ʻoki ʻē aʻe. ʻenehana lihi.
hoʻokau
He mau palena ko mākou noiʻi. ʻO ka mea mua, hoʻoholo ʻia nā ʻike e nā paʻi i koho ʻia no ka loiloi hope. He mea paʻakikī ka hopu ʻana i nā haʻawina kūpono āpau e pili ana i nā drones mahiʻai, ʻoi aku ka poʻe i kuhikuhi ʻole ʻia ma ka waihona Scopus. Eia hou, ua kaupalena ʻia ke kaʻina o ka hōʻiliʻili ʻikepili i ka hoʻonohonoho ʻana i nā huaʻōlelo hulina, ʻaʻole paha i komo a alakaʻi i nā ʻike inconclusive. No laila, pono e nānā pono nā haʻawina e hiki mai ana i ke kumu kumu o ka hōʻiliʻili ʻikepili e hana ai
ʻoi aku ka hilinaʻi o nā hopena. ʻO kekahi palena ʻē aʻe e pili ana i nā puke hou me ka helu haʻahaʻa o nā huaʻōlelo. Hoʻopili ʻia ka loiloi bibliometric i nā paʻi mua ʻana i ka loaʻa ʻana o nā huaʻōlelo hou aku i nā makahiki. Pono nā haʻawina hou i kekahi manawa e huki i ka nānā a hōʻiliʻili i nā huaʻōlelo. No laila, ʻaʻole e hoʻokumu ʻia nā haʻawina hou e lawe mai ana i kahi hoʻololi paradigm i nā hana koʻikoʻi he ʻumi. Loaʻa kēia palena i ka nānā ʻana i nā kikowaena noiʻi wikiwiki e like me nā drones mahiʻai. E like me kā mākou kūkākūkā ʻana iā Scopus e aʻo i ka palapala no kēia hana, hiki i nā mea noiʻi e hiki mai ana ke noʻonoʻo ʻokoʻa
ʻikepili, e like me ka Web of Science a me IEEE Xplore, e hoʻonui i ka ʻike a hoʻonui i ke ʻano noiʻi.
Hiki paha i nā haʻawina bibliometric ke noʻonoʻo i nā kumu ʻike koʻikoʻi e like me nā pepa kūkā, nā mokuna, a me nā puke e hoʻopuka i nā ʻike hou. ʻOiai ʻo ka palapala ʻāina a me ka noiʻi ʻana i nā puke paʻi honua e pili ana i nā drones mahiʻai, ʻaʻole i hōʻike kā mākou ʻike i nā kumu ma hope o nā hoʻopuka naʻauao o nā kulanui. Hāʻawi kēia i ke ala i kahi wahi hou o ka noiʻi ʻana i ka wehewehe ʻana i ke kumu i ʻoi aku ka maikaʻi o kekahi mau kula ma mua o nā mea ʻē aʻe i ka noiʻi ʻana e pili ana i ka mahiʻai.
drones. Eia kekahi, hiki i nā haʻawina i ka wā e hiki mai ana ke hāʻawi i nā ʻike i ka hiki o nā drones e hoʻonui i ka hoʻomau ʻana i ka mahiʻai ma nā ʻano like ʻole e like me ka nānā ʻana i ke kaiapuni, ka mālama ʻana i nā mea kanu, a me ka palapala ʻāina weed e like me ka mea i hōʻike ʻia e nā mea noiʻi (Chamuah & Singh, 2019; Islam et al., 2021; Popescu et al., 2020; J. Su, Liu, et al., 2018b). Ma muli o ka hiki ʻole o ka nānā ʻana i nā kikokikona ma muli o ka nui o nā pepa i koho ʻia, pono e noʻonoʻo ʻia nā palapala ʻōnaehana e nānā i ka
nā ʻano noiʻi i hoʻohana ʻia a me ke komo ʻana o ka poʻe mahiʻai i nā haʻawina mua. I ka pōkole, ʻo kā mākou loiloi o ka noiʻi drone e hōʻike i nā loulou ʻike ʻole o kēia kino ʻike. No laila, kōkua kēia loiloi i ka wehe ʻana i nā pilina ma waena o nā puke a e ʻimi i ke ʻano o ka naʻauao o ke kahua noiʻi. Hōʻike pū ia i ka pilina ma waena o nā ʻano like ʻole o ka palapala, e like me nā huaʻōlelo a nā mea kākau, pili, a me nā ʻāina.
Hoʻolaha o ka hoihoi hoʻokūkū
Hōʻike nā mea kākau ʻaʻole lākou i ʻike e hoʻokūkū i nā hoihoi kālā a i ʻole nā pilina pilikino i hiki ke ʻike ʻia e hoʻohuli i ka hana i hōʻike ʻia i loko o kēia pepa.
Pākuʻi 1
TITLE-ABS-KEY (((drone* A i ʻole "kaʻa lewa ʻole" a i ʻole uav * A i ʻole "pūnaewele mokulele ʻole.” OR uas A I ʻole "mau mokulele hoʻokele mamao”) A (mahiʻai A mahiʻai OR mahiʻai OR mea mahiʻai))) A ME (KE KOE (PUBYEAR, 2022)) A me (LIMIT-TO (LANGUAGE, “English”)).
E hoʻomaopopo '
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