Journal of Intelligent Systems and Internet of Things

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https://doi.org/10.54216/JISIoT

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2690-6791ISSN (Online) 2769-786XISSN (Print)

Volume 14 , Issue 1 , PP: 168-184, 2025 | Cite this article as | XML | Html | PDF | Full Length Article

Energy Assessment based Smart Sustainable Production in Wireless Environment Using Internet of Agricultural Things (IoAT)

Ahmed N. Rashid 1 * , Ahmed Mahdi Jubair 2 *

  • 1 Department of Computer Networks Systems, College of Computer Science and Information Technology, University of Anbar, Anbar, 31001, Iraq - (rashidisgr@uoanbar.edu.iq)
  • 2 Department of Computer Networks Systems, College of Computer Science and Information Technology, University of Anbar, Anbar, 31001, Iraq - (ahmed.mahdi@uoanbar.edu.iq)
  • Doi: https://doi.org/10.54216/JISIoT.140113

    Received: February 18, 2024 Revised: April 27, 2024 Accepted: July 17, 2024
    Abstract

    The attainment of smart sustainable production of energy is the goal, which is being pursued globally. In the field of agricultural system, several challenges are present and as well, it is combined with the climatic crises. In general, the renewable energy resources is the origin of energy production and consumption so that using this energy source it is possible to improve the ecologically and social agriculture. Due to the expansion of renewable energy, the concept of Agrivoltaic System is created which convert the food production to energy generation process. Currently many of the research are developed to increase the crop yield and energy production. In this article, we concentrate on intelligent farming in agrivoltaic system with the help of Internet of Agricultural Things (IoAT). It focuses on newer preliminary methods like fluid dynamic system, improved photovoltaic (PV) module, land equivalent ratio analysis and shading ratio calculation. In IoAT based system, crop field analysis, energy production model, sensor localization process, cost optimization and fault diagnosis processes are concentrated. So that the effective outcomes are attained in the cultivation of crops like melon, bean, millet, and cucumber. The parameters, which are calculated in the results analysis, are shading ratio and temperature, crops-based analysis, and energy-based analysis. With the help of IoAT system both, the crop yield and electricity production is increased.

    Keywords :

    Agrivoltaic system, Renewable energy resources, Intelligent farming, Internet of agricultural things (IoAT)

    References

    [1]          Marco Cossu, Maria Teresa Tiloca, Andrea Cossu, Paola A. Deligios, Tore Pala, Luigi Ledda, “Increasing the agricultural sustainability of closed agrivoltaic systems with the integration of vertical farming: A case study on baby-leaf lettuce,” Applied Energy, vol. 344, no.121278, pp.1-14, 2023, https://doi.org/10.1016/j.apenergy.2023.121278.

    [2]          Khalid, M. M., & Karan , O. (2023). Deep Learning for Plant Disease Detection. International Journal of Mathematics, Statistics, and Computer Science, 2, 75–84. https://doi.org/10.59543/ijmscs.v2i.8343

    [3]          Julieta Schallenberg-Rodriguez, José-Julio Rodrigo-Bello, B. Del Río-Gamero, “Agrivoltaic: How much electricity could photovoltaic greenhouses supply,” Energy Reports, vol. 9, pp. 5420-5431, 2023, https://doi.org/10.1016/j.egyr.2023.04.374.

    [4]          Sangik Lee, Jong-hyuk Lee, Youngjoon Jeong, Dongsu Kim, Byung-hun Seo, Ye-jin Seo, Taejin Kim, Won Choi, “Agrivoltaic system designing for sustainability and smart farming: Agronomic aspects and design criteria with safety assessment,” Applied Energy, vol. 341, no.121130, pp1-14, 2023,  https://doi.org/10.1016/j.apenergy.2023.121130.

    [5]          Ameen, A.H., Mohammed, M.A. and Rashid, A.N., 2024. Enhancing Security in IoMT: A Blockchain-Based Cybersecurity Framework for Machine Learning-Driven ECG Signal Classification. Fusion: Practice and Applications, 14(1), pp.221-251.

    [6]          Sebastian Zainali, Omar Qadir, Sertac Cem Parlak, Silvia Ma Lu, Anders Avelin, Bengt Stridh, Pietro Elia Campana, “Computational fluid dynamics modelling of microclimate for a vertical agrivoltaic system,” Energy Nexus, vol. 9, no.100173, 2023, https://doi.org/10.1016/j.nexus.2023.100173.

    [7]          Ahmed, Sahar Hamad, and Ahmed Noori Rashid. "Hybrid K-Mean PSO Clustering Algorithm for Energy-Efficient of Object Tracking in WSNs." 2023 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME). IEEE, 2023

    [8]          Y. Elamri, B. Cheviron, J.-M. Lopez, C. Dejean, G. Belaud, “Water budget and crop modelling for agrivoltaic systems: Application to irrigated lettuces,” Agricultural Water Management, vol. 208, pp. 440-453, 2018,  https://doi.org/10.1016/j.agwat.2018.07.001.

    [9]          Daisuke Yajima, Teruya Toyoda, Masaaki Kirimura, Kenji Araki, Yasuyuki Ota, Kensuke Nishioka,“Agrivoltaic system: Estimation of photosynthetic photon flux density under solar panels based on solar irradiation data using all-climate solar spectrum model,” Cleaner Engineering and Technology, vol. 12, no. 100594, 2023, https://doi.org/10.1016/j.clet.2022.100594.

    [10]       J.S. Botero-Valencia, M. Mejia-Herrera, Joshua M. Pearce, “Low cost climate station for smart agriculture applications with photovoltaic energy and wireless communication,” Hardware X, vol. 11, 2022,  https://doi.org/10.1016/j.ohx.2022.e00296.

    [11]       Fahad, Majed Hamed, and Ahmed Noori Rashid. "Reduce the Spread Risk of COVID-19 based on Clinical Fusion Data and Monitoring System in Wireless Sensor Network." Fusion: Practice and Applications 11.1 (2023): 26-6.

    [12]       Eduardo F. Fernández, Antonio Villar-Fernández, Jesús Montes-Romero, Laura Ruiz-Torres, Pedro M. Rodrigo, Antonio J. Manzaneda, Florencia Almonacid, “Global energy assessment of the potential of photovoltaics for greenhouse farming,” Applied Energy, vol. 309, no. 118474, 2022, https://doi.org/10.1016/j.apenergy.2021.118474.

    [13]       Lakhan, A., Rashid, A. N., Mohammed, M. A., Zebari, D. A., Deveci, M., Wang, L., ... & Martinek, R. (2024). Multi-agent reinforcement learning framework based on information fusion biometric ticketing data in different public transport modes. Information Fusion, 110, 102471

    [14]       Chong Seok Choi, Sujith Ravi, Iskandar Z. Siregar, Fifi Gus Dwiyanti, Jordan Macknick, Michael Elchinger, Nicholas C. Davatzes, “Combined land use of solar infrastructure and agriculture for socioeconomic and environmental co-benefits in the tropics,” Renewable and Sustainable Energy Reviews, vol. 151, no. 111610, 2021,  https://doi.org/10.1016/j.rser.2021.111610.

    [15]       I.K. Okakwu, A.S. Alayande, D.O. Akinyele, O.E. Olabode, J.O. Akinyemi, “Effects of total system head and solar radiation on the techno-economics of PV groundwater pumping irrigation system for sustainable agricultural production”, Scientific African, vol. 16, 2022,  https://doi.org/10.1016/j.sciaf.2022.e01118.

    [16]       Anne-Kathrin Schneider, Felix Klabunde, Lennart Buck, Maren Ohlhoff, Larissa Reis, Madita Olvermann, Simone Kauffeld, Bernd Engel, Gerhard Glatzel, Boris Schröder, Ludger Frerichs, “Drawing transformation pathways for making use of joint effects of food and energy production with biodiversity agriphotovoltaics and electrified agricultural machinery,” Journal of Environmental Management, vol. 335, no. 117539, 2023, https://doi.org/10.1016/j.jenvman.2023.117539.

    [17]       D. Oudes, A. van den Brink, S. Stremke, “Towards a typology of solar energy landscapes: Mixed-production, nature based and landscape inclusive solar power transitions,” Energy Research & Social Science, vol. 91, no. 102742, 2022, https://doi.org/10.1016/j.erss.2022.102742.

    [18]       Xueqian Fu, Haosen Niu, “Key technologies and applications of agricultural energy Internet for agricultural planting and fisheries industry,” Information Processing in Agriculture, no. 10004, 2022, https://doi.org/10.1016/j.inpa.2022.10.004.

    [19]       O. Friha, M. A. Ferrag, L. Shu, L. Maglaras and X. Wang, "Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies," in IEEE/CAA Journal of Automatica Sinica, vol. 8, no. 4, pp. 718-752, April 2021, doi: 10.1109/JAS.2021.1003925.

    [20]       K. Huang et al., "Photovoltaic Agricultural Internet of Things Towards Realizing the Next Generation of Smart Farming," in IEEE Access, vol. 8, pp. 76300-76312, 2020, doi: 10.1109/ACCESS.2020.2988663.

    [21]       Jayaraman, P.P.; Yavari, A.; Georgakopoulos, D.; Morshed, A.; Zaslavsky, “A Internet of Things Platform for Smart Farming: Experiences and Lessons Learnt,” Sensors, vol. 16, no. 1884, 2016, https://doi.org/10.3390/s16111884.

    [22]       Romain Carrausse, Xavier Arnauld de Sartre. “Does agrivoltaism reconcile energy and agriculture? Lessons from a French case study,” Energy, Sustainability and Society, vol. 13, no. , pp.8, 2023, doi: 10.1186/s13705-023-00387-3.

    [23]       Pascaris, A.S., Schelly, C., Rouleau, M. et al. “Do agrivoltaics improve public support for solar? A survey on perceptions, preferences, and priorities,” GRN TECH RES SUSTAIN 2, vol. 8, 2022, https://doi.org/10.1007/s44173-022-00007-x

    [24]       Odysseas Alexandros Katsikogiannis, Hesan Ziar, Olindo Isabella, “Integration of bifacial photovoltaics in agrivoltaic systems: A synergistic design approach,” Applied Energy, vol. 309, no. 118475, 2022,  https://doi.org/10.1016/j.apenergy.2021.118475.

    [25]       Max Trommsdorff, Jinsuk Kang, Christian Reise, Stephan Schindele, Georg Bopp, Andrea Ehmann, Axel Weselek, Petra Högy, Tabea Obergfell, “Combining food and energy production: Design of an agrivoltaic system applied in arable and vegetable farming in Germany,” Renewable and Sustainable Energy Reviews, vol. 140, no.110694, 2021,  https://doi.org/10.1016/j.rser.2020.110694.

    [26]       Stefano Amaducci, Xinyou Yin, Michele Colauzzi, “Agrivoltaic systems to optimise land use for electric energy production,” Applied Energy, vol. 220, pp. 545-561, 2018, https://doi.org/10.1016/j.apenergy.2018.03.081.

    [27]       Agostini, M. Colauzzi, S. Amaducci, “Innovative agrivoltaic systems to produce sustainable energy: An economic and environmental assessment,” Applied Energy, vol. 281, no.116102, 2021,  https://doi.org/10.1016/j.apenergy.2020.116102.

    [28]       van de Ven, DJ., Capellan-Peréz, I., Arto, I. et al. “The potential land requirements and related land use change emissions of solar energy,”vol. 11, no. 2907, 2021, https://doi.org/10.1038/s41598-021-82042-5.

    [29]       Ahmed, Sahar Hamad, and Ahmed Noori Rashid. "Prediction of Single Object Tracking Based on Learning Approach in Wireless Sensor Networks." 2021 14th International Conference on Developments in eSystems Engineering (DeSE). IEEE, 2021.

    Cite This Article As :
    N., Ahmed. , Mahdi, Ahmed. Energy Assessment based Smart Sustainable Production in Wireless Environment Using Internet of Agricultural Things (IoAT). Journal of Intelligent Systems and Internet of Things, vol. , no. , 2025, pp. 168-184. DOI: https://doi.org/10.54216/JISIoT.140113
    N., A. Mahdi, A. (2025). Energy Assessment based Smart Sustainable Production in Wireless Environment Using Internet of Agricultural Things (IoAT). Journal of Intelligent Systems and Internet of Things, (), 168-184. DOI: https://doi.org/10.54216/JISIoT.140113
    N., Ahmed. Mahdi, Ahmed. Energy Assessment based Smart Sustainable Production in Wireless Environment Using Internet of Agricultural Things (IoAT). Journal of Intelligent Systems and Internet of Things , no. (2025): 168-184. DOI: https://doi.org/10.54216/JISIoT.140113
    N., A. , Mahdi, A. (2025) . Energy Assessment based Smart Sustainable Production in Wireless Environment Using Internet of Agricultural Things (IoAT). Journal of Intelligent Systems and Internet of Things , () , 168-184 . DOI: https://doi.org/10.54216/JISIoT.140113
    N. A. , Mahdi A. [2025]. Energy Assessment based Smart Sustainable Production in Wireless Environment Using Internet of Agricultural Things (IoAT). Journal of Intelligent Systems and Internet of Things. (): 168-184. DOI: https://doi.org/10.54216/JISIoT.140113
    N., A. Mahdi, A. "Energy Assessment based Smart Sustainable Production in Wireless Environment Using Internet of Agricultural Things (IoAT)," Journal of Intelligent Systems and Internet of Things, vol. , no. , pp. 168-184, 2025. DOI: https://doi.org/10.54216/JISIoT.140113