| [1] |
Khan N, Ray RL, Sargani GR, Ihtisham M, Khayyam M, et al. 2021. Current progress and future prospects of agriculture technology: gateway to sustainable agriculture. Sustainability 13(9):4883 doi: 10.3390/su13094883 |
| [2] |
Ashraf SA, Siddiqui AJ, Elkhalifa AEO, Khan MI, Patel M, et al. 2021. Innovations in nanoscience for the sustainable development of food and agriculture with implications on health and environment. Science of The Total Environment 768:144990 doi: 10.1016/j.scitotenv.2021.144990 |
| [3] |
Hassan QF. 2018. Internet of things A to Z: technologies and applications. US: John Wiley & Sons. 672 pp. doi: 10.1002/9781119456735 |
| [4] |
Ristaino JB, Anderson PK, Bebber DP, Brauman KA, Cunniffe NJ, et al. 2021. The persistent threat of emerging plant disease pandemics to global food security. Proceedings of the National Academy of Sciences of the United States of America 118(23):e2022239118 doi: 10.1073/pnas.2022239118 |
| [5] |
Hathaway MD. 2016. Agroecology and permaculture: addressing key ecological problems by rethinking and redesigning agricultural systems. Journal of Environmental Studies and Sciences 6:239−50 doi: 10.1007/s13412-015-0254-8 |
| [6] |
Paul K, Chatterjee SS, Pai P, Varshney A, Juikar S, et al. 2022. Viable smart sensors and their application in data driven agriculture. Computers and Electronics in Agriculture 198:107096 doi: 10.1016/j.compag.2022.107096 |
| [7] |
Gorjian S, Minaei S, MalehMirchegini L, Trommsdorff M, Shamshiri RR. 2020. Applications of solar PV systems in agricultural automation and robotics. In Photovoltaic Solar Energy Conversion, eds Gorjian S, Shukla A. UK: Academic Press. pp. 191−235. doi: 10.1016/B978-0-12-819610-6.00007-7 |
| [8] |
Shaikh TA, Rasool T, Lone FR. 2022. Towards leveraging the role of machine learning and artificial intelligence in precision agriculture and smart farming. Computers and Electronics in Agriculture 198:107119 doi: 10.1016/j.compag.2022.107119 |
| [9] |
Jalal MA, Abdulmajeed OT, Jasim NA. 2022. Effective use of fertilizers and analysis of soil using precision agriculture techniques. Iraqi Journal of Soil Science 22(1):157−64 |
| [10] |
AlZu’bi S, Hawashin B, Mujahed M, Jararweh Y, Gupta BB. 2019. An efficient employment of internet of multimedia things in smart and future agriculture. Multimedia Tools and Applications 78:29581−605 doi: 10.1007/s11042-019-7367-0 |
| [11] |
Ragazou K, Garefalakis A, Zafeiriou E, Passas I. 2022. Agriculture 5.0: a new strategic management mode for a cut cost and an energy efficient agriculture sector. Energies 15(9):3113 doi: 10.3390/en15093113 |
| [12] |
Rose DC, Chilvers J. 2018. Agriculture 4.0: broadening responsible innovation in an era of smart farming. Frontiers in Sustainable Food Systems 2:87 doi: 10.3389/fsufs.2018.00087 |
| [13] |
Yang X, Shu L, Chen J, Ferrag MA, Wu J, et al. 2021. A survey on smart agriculture: development modes, technologies, and security and privacy challenges. IEEE/CAA Journal of Automatica Sinica 8(2):273−302 doi: 10.1109/JAS.2020.1003536 |
| [14] |
Al-Mashhadany SA, Hasan HA, Al-Sammarraie MAJ. 2024. Using machine learning algorithms to predict the sweetness of bananas at different drying times. Journal of Ecological Engineering 25(6):231−38 doi: 10.12911/22998993/187789 |
| [15] |
Hassan SI, Alam MM, Illahi U, Al Ghamdi MA, Almotiri SH, et al. 2021. A systematic review on monitoring and advanced control strategies in smart agriculture. IEEE Access 9:32517−48 doi: 10.1109/ACCESS.2021.3057865 |
| [16] |
Srbinovska M, Gavrovski C, Dimcev V, Krkoleva A, Borozan V. 2015. Environmental parameters monitoring in precision agriculture using wireless sensor networks. Journal of Cleaner Production 88:297−307 doi: 10.1016/j.jclepro.2014.04.036 |
| [17] |
Wu DD, Olson DL, Birge JR. 2013. Risk management in cleaner production. Journal of Cleaner Production 53:1−6 doi: 10.1016/j.jclepro.2013.02.014 |
| [18] |
Ferrag MA, Shu L, Yang X, Derhab A, Maglaras L. 2020. Security and privacy for green IoT-based agriculture: review, blockchain solutions, and challenges. IEEE Access 8:32031−53 doi: 10.1109/ACCESS.2020.2973178 |
| [19] |
Ashworth AJ, Lindsay KR, Popp MP, Owens PR. 2018. Economic and environmental impact assessment of tractor guidance technology. Agricultural & Environmental Letters 3(1):180038 doi: 10.2134/ael2018.07.0038 |
| [20] |
Balafoutis A, Beck B, Fountas S, Vangeyte J, Van der Wal T, et al. 2017. Precision agriculture technologies positively contributing to GHG emissions mitigation, farm productivity and economics. Sustainability 9(8):1339 doi: 10.3390/su9081339 |
| [21] |
Al-Sammarraie MAJ, Kırılmaz H. 2023. Technological advances in soil penetration resistance measurement and prediction algorithms. Reviews in Agricultural Science 11:93−105 doi: 10.7831/ras.11.0_93 |
| [22] |
Colaço AF, Molin JP. 2017. Variable rate fertilization in citrus: a long term study. Precision Agriculture 18:169−91 doi: 10.1007/s11119-016-9454-9 |
| [23] |
Guerrero A, De Neve S, Mouazen AM. 2021. Data fusion approach for map-based variable-rate nitrogen fertilization in barley and wheat. Soil and Tillage Research 205:104789 doi: 10.1016/j.still.2020.104789 |
| [24] |
Garrigues E, Corson MS, Angers DA, van der Werf HMG, Walter C. 2012. Soil quality in Life Cycle Assessment: towards development of an indicator. Ecological Indicators 18:434−42 doi: 10.1016/j.ecolind.2011.12.014 |
| [25] |
Gasso V, Oudshoorn FW, Sørensen CAG, Pedersen HH. 2014. An environmental life cycle assessment of controlled traffic farming. Journal of Cleaner Production 73:175−82 doi: 10.1016/j.jclepro.2013.10.044 |
| [26] |
Medel-Jiménez F, Piringer G, Gronauer A, Barta N, Neugschwandtner RW, et al. 2022. Modelling soil emissions and precision agriculture in fertilization life cycle assessment - a case study of wheat production in Austria. Journal of Cleaner Production 380:134841 doi: 10.1016/j.jclepro.2022.134841 |
| [27] |
Li A, Duval BD, Anex R, Scharf P, Ashtekar JM, et al. 2016. A case study of environmental benefits of sensor-based nitrogen application in corn. Journal of Environmental Quality 45(2):675−83 doi: 10.2134/jeq2015.07.0404 |
| [28] |
Medel-Jiménez F, Krexner T, Gronauer A, Kral I. 2024. Life cycle assessment of four different precision agriculture technologies and comparison with a conventional scheme. Journal of Cleaner Production 434:140198 doi: 10.1016/j.jclepro.2023.140198 |
| [29] |
Reckleben Y, Noack PO. 2012. RTK correction data networks for comprehensive, high-precision position determination in agriculture. Landtechnik 67(3):162−65 |
| [30] |
Shockley J, Dillon CR, Stombaugh T, Shearer S. 2012. Whole farm analysis of automatic section control for agricultural machinery. Precision Agriculture 13:411−20 doi: 10.1007/s11119-011-9256-z |
| [31] |
Baillie CP, Thomasson JA, Lobsey CR, McCarthy CL, Antille DL. 2018. A review of the state of the art in agricultural automation. Part IV: sensor-based nitrogen management technologies. Proc. ASABE 2018 Annual International Meeting, 2018, Detroit, Michigan. American Society of Agricultural and Biological Engineers, St. Joseph, MI. doi: 10.13031/aim.201801589 |
| [32] |
Al-Sammarraie MAJ, Al-Aani F, Al-Mashhadany SA. 2023. Determine, predict and map soil pH level by fiber optic sensor. IOP Conference Series: Earth and Environmental Science 1225(1):012104 doi: 10.1088/1755-1315/1225/1/012104 |
| [33] |
Weersink A, Fraser E, Pannell D, Duncan E, Rotz S. 2018. Opportunities and challenges for big data in agricultural and environmental analysis. Annual Review of Resource Economics 10:19−37 doi: 10.1146/annurev-resource-100516-053654 |
| [34] |
Bazargani K, Deemyad T. 2024. Automation's impact on agriculture: opportunities, challenges, and economic effects. Robotics 13(2):33 doi: 10.3390/robotics13020033 |
| [35] |
Villa-Henriksen A, Edwards GTC, Pesonen LA, Green O, Sørensen CAG. 2020. Internet of Things in arable farming: implementation, applications, challenges and potential. Biosystems Engineering 191:60−84 doi: 10.1016/j.biosystemseng.2019.12.013 |
| [36] |
Wang SC, Lin YJ, Yan KQ, Chen CW. 2019. Security enhancement of internet of Things using service level agreements and lightweight security. In Advances in Information and Communication Networks, vol 887, eds Arai K, Kapoor S, Bhatia R. FICC 2018. Cham: Springer. pp. 221–35. doi: 10.1007/978-3-030-03405-4_15 |
| [37] |
Zong Z, Fares R, Romoser B, Wood J. 2014. FastStor: improving the performance of a large scale hybrid storage system via caching and prefetching. Cluster Computing 17:593−604 doi: 10.1007/s10586-013-0304-5 |
| [38] |
West J. 2018. A prediction model framework for cyber-attacks to precision agriculture technologies. Journal of Agricultural & Food Information 19(4):307−30 doi: 10.1080/10496505.2017.1417859 |
| [39] |
Li X, Chen S, Guo L. 2014. Technological innovation of agricultural information service in the age of big data. Journal of Agricultural Science & Technology 16(4):10−15 |
| [40] |
Ko D, Kwak Y, Song S. 2014. Real time traceability and monitoring system for agricultural products based on wireless sensor network. International Journal of Distributed Sensor Networks 10(6):832510 doi: 10.1155/2014/832510 |
| [41] |
Muangprathub J, Boonnam N, Kajornkasirat S, Lekbangpong N, Wanichsombat A, et al. 2019. IoT and agriculture data analysis for smart farm. Computers and Electronics in Agriculture 156:467−74 doi: 10.1016/j.compag.2018.12.011 |
| [42] |
Ariff MH, Ismail I. 2018. RFID application development for a livestock monitoring system. In Bioresources Technology in Sustainable Agriculture Point, eds Abdullah MFF, Ali MTB, Yusof FZM. Pleasant, NJ: Apple Academic Press. pp. 81−94. doi: 10.1201/9781315365961-6 |
| [43] |
Kang M, Fan XR, Hua J, Wang H, Wang X, et al. 2018. Managing traditional solar greenhouse with CPSS: a just-for-fit philosophy. IEEE Transactions on Cybernetics 48(12):3371−80 doi: 10.1109/TCYB.2018.2858264 |
| [44] |
Li F, Liu Q, Dong S, Cheng H. 2018. Agricultural development status and key cooperation directions between China and countries along "The Belt and Road". IOP Conference Series: Earth and Environmental Science 190(1):012058 doi: 10.1088/1755-1315/190/1/012058 |
| [45] |
Patrício DI, Rieder R. 2018. Computer vision and artificial intelligence in precision agriculture for grain crops: a systematic review. Computers and Electronics in Agriculture 153:69−81 doi: 10.1016/j.compag.2018.08.001 |
| [46] |
Al-Sammarraie MAJ, Gierz ŁA, Özbek O, Kırılmaz H. 2024. Power predicting for power take-off shaft of a disc maize silage harvester using machine learning. Advances in Science and Technology Research Journal 18(5):1−9 doi: 10.12913/22998624/188666 |
| [47] |
Castanedo F. 2013. A review of data fusion techniques. The Scientific World Journal 2013(1):704504 doi: 10.1155/2013/704504 |
| [48] |
Gierz Ł, Al-Sammarraie MAJ, Özbek O, Markowski P. 2024. The use of image analysis to study the effect of moisture content on the physical properties of grains. Scientific Reports 14(1):11673 doi: 10.1038/s41598-024-60852-7 |
| [49] |
Arvanitis KG, Symeonaki EG. 2020. Agriculture 4.0: the role of innovative smart technologies towards sustainable farm management. The Open Agriculture Journal 14(1):130−35 doi: 10.2174/1874331502014010130 |
| [50] |
Alreshidi E. 2019. Smart sustainable agriculture (SSA) solution underpinned by internet of things (IoT) and artificial intelligence (AI). International Journal of Advanced Computer Science and Applications 10(5):93−102 doi: 10.14569/IJACSA.2019.0100513 |
| [51] |
Al-Sammarraie MAJ, Jasim NA. 2021. Determining the efficiency of a smart spraying robot for crop protection using image processing technology. INMATEH-Agricultural Engineering 64(2):365−74 doi: 10.35633/inmateh-64-36 |
| [52] |
Ji C, Shao Q, Sun J, Liu S, Pan L, et al. 2016. Device data ingestion for industrial big data platforms with a case study. Sensors 16(3):279 doi: 10.3390/s16030279 |
| [53] |
Delgado JA, Short NM Jr, Roberts DP, Vandenberg B. 2019. Big data analysis for sustainable agriculture on a geospatial cloud framework. Frontiers in Sustainable Food Systems 3:54 doi: 10.3389/fsufs.2019.00054 |
| [54] |
Lu H, Tang L, Whitham SA, Mei Y. 2017. A robotic platform for corn seedling morphological traits characterization. Sensors 17(9):2082 doi: 10.3390/s17092082 |
| [55] |
Palli P, Liew CT, Drozda A, Mwunguzi H, Pitla SK, et al. 2019. Robotic gantry for automated imaging, sensing, crop input application, and high-throughput analysis. Proc. 2019 ASABE Annual International Meeting, Boston, 2019. American Society of Agricultural and Biological Engineers, St. Joseph, MI. doi: 10.13031/aim.201901519 |
| [56] |
Treiber M, Hillerbrand F, Bauerdick JJ, Bernhardt H. 2019. On the current state of agricultural robotics in crop farming chances and risks. Proc. 47th International Symposium "Actual Tasks on Agricultural Engineering", Opatija, Croatia, 2019. pp. 27−33. |
| [57] |
Jin Y, Liu J, Xu Z, Yuan S, Li P, et al. 2021. Development status and trend of agricultural robot technology. International Journal of Agricultural and Biological Engineering 14(4):1−19 doi: 10.25165/j.ijabe.20211404.6821 |
| [58] |
Goedde L, Katz J, Ménard A, Revellat J. 2020. Agriculture's connected future: how technology can yield new growth. www.mckinsey.com/industries/agriculture/our-insights/agricultures-connected-future-how-technology-can-yield-new-growth# |
| [59] |
Revich J, Koort R, Archambault P, Samuelson A, Nannizzi M, et al. 2016. Precision farming: cheating malthus with digital agriculture. Equity Research, The Goldman Sachs Group, Inc., US. www.gspublishing.com/content/research/en/reports/2016/07/13/6e4fa167-c7ad-4faf-81de-bfc6acf6c81f.pdf |