Behrooznia, A.H.G., & Hashezadeh khoorasgani, G.H., & Radfar, R. (2021). Explain the development of technology in the field of pharmaceutical industry and its role in sustainable social and economic development. Journal of Iranian Social Development Studies, 13(52), 277-290. [In Persian] htpp://doi.org/10.30495/jisds.2022.56207.11359.
Dehghani, B. (2020). Emerging technologies in agriculture and food with a supply chain approach. Tehran, Iarn: tarbiate modir publication.
Didegah, S.A., & Tahmurt, S. (2022). Identifying and leveling the factors affecting the development of emerging technologies in agriculture with a supply chain approach. Journal of Industry and University, 51(4), 187-207. [In Persian] htpp://doi.org/20.1001.1.27170446.1400.14.51.3.0.
Dong, Y., Hou, J., Zhang, N., & Zhang, M. (2020). Research on How Human Intelligence, Consciousness, and Cognitive Computing Affect the Development of Artificial Intelligence. CComplexity, 1, 1-10.
https://doi.org/10.1155/2020/1680845.
Dorri, A., Kanhere, S.S., Jurdak, R., & Gauravaram, P. A. (2019). Lightweight Scalable Blockchain for IoT security and anonymity. Journal of Parallel and Distributed Computing, 134, 180–19.
https://doi.org/10.1016/j.jpdc.2019.08.005.
FAO. (2017). The future of food and agriculture–Trends and challenges. Annual Report. Retrieved from https://reliefweb.int/report/world/future-food-and-agriculture-trends-and-challenges?gad_source=1&gclid=CjwKCAjwqf20BhBwEiwAt7dtdcnwtIf3frBjzR2qBnM4uPqge0gBtqekrwdzddSq77CGPWogXI8BDxoCBs0QAvD_BwE
Francisco, G.E., ́Htuna, N.N., Schlenzb, F., Kasimatic, A., & Verberta, K. (2019). A Review of Visualisations in Agricultural Decision Support Systems: an HCI Perspective. Computers and electronics in agriculture, 163, 104844.
https://doi.org/10.1016/j.compag.2019.05.053.
Ghisellini, P., Cialani, C., & Ulgiati, S. (2016). A review on circular economy: the expected transition to a balanced interplay of environmental and economic systems. Journal of Cleaner Production, 114, 11–32. htpp://doi.org/10.1016/j.jclepro.2015.09.007
Gholamnejad, M., Movahedi, M., Manteghi, M., & AliYari, S. (2022). Presenting a Model for Measuring the Success of Technology Transfer in Iran's Petrochemical Industry. Journal of Technology Development Management, 9(4), 75-99. [In Persian] htpp://doi.org/10.22104/jtdm.2022.4880.2788
Gilchrist, A. (2018). The supply chain in the industrial revolution, from warehouse shelves to expansion in the world. Translated by Ahmad Jafaranjad, Ramin Najizadeh, Reza Karimi. Tehran, Iran: Industrial Management Organization publication. [In Persian]
Hassan, S. I., Alam, M. M., Illahi, U., Al Ghamdi, M. A., Almotiri, S. H., & Su’ud, M. M. (2021). A Systematic Review on Monitoring and Advanced Control Strategies in Smart Agriculture. IEEE Access, 9, 32517–32548. htpp://doi.org/10.1109/ACCESS.2021.3057865.
Hatami, P., & Hosseini, A. (2018). The role of Internet of Things in promoting the agricultural industry in the field of smart irrigation (and analysis of its results in Iran). Master's thesis. Qazvin, Iran: Ghiyasuddin Jamshid Kashani University. [In Persian]
Mohammadian, A., Heidary Dahooie, J., & Ghorbani, A. (2020). Prioritizing the Applications of Internet of Things in the Agriculture by Using Sustainable Development Indicators. Iranian journal of agricultural economics and development research, 51(4), 745-759. [In Persian] htpp://doi.org/
10.22059/IJAEDR.2020.282000.668759.
Jamshidi, B., & Dehghani Sanij, H. (2019). Big data based on Internet of Things from the perspective of smart agriculture. Technological growth, 16(63), 12-22. [In Persian]
htpp://doi.org/10.52547/jstpi.20875.16.63.12
Kagermann, H. (2015). Change through digitization—value creation in the age of Industry 4.0. Management of Permanent Change, 23–45. htpp://doi.org/10.1007/978-3-658-05014-6_2.
Kasinathan, T. Singaraju, D., & Srinivasulu-Reddy, U. (2020). Insect classification and detection in field crops using modern machine learning.
Information Processing in Agriculture, 8(3), 446-457.
https://doi.org/10.1016/j.inpa.2020.09.006.
Korhonen, J., Nuur, C., Feldmann, A., & Birkie, S.E. (2018). Circular economy as an Essen tially contested concept. Journal of Cleaner Production, 175, 544–552. htpp://doi.org/10.1016/j.jclepro.2017.12.111.
Lasi, H., Fettke, P., Kemper, H.G., Feld, T. and Hoffmann, M. (2014) Industry 4.0. Business & Information Systems Engineering, 6, 239-242. https://doi.org/10.1007/s12599-014-0334-4.
Makate, C. (2019). Effective scaling of climate smart agriculture innovations in African smallholder agriculture: A review of approaches, policy and institutional strategy needs. Environmental Science & Policy, 96, 37–51. htpp://doi.org/10.1016/j.envsci.2019.01.014.
Mars, M.M., & Ball, A.L. (2016). Ways of Knowing, Sharing, and Translating Agricultural Knowledge and Perspectives: Alternative Epistemologies across Non-formal and Informal Settings Journal of Agricultural Education, 57(1), 56-72. htpp://doi.org/10.5032/jae.2016.010 .
Martinez-Mosquera, D., Navarrete, R., & Lujan-Mora, S. (2020). Modeling and Management Big Data in Databases—A Systematic Literature Review. Sustainability, 12(2), 634.
htpp://doi.org/10.3390/su12020634.
Jha, N., Prashar, D., Khalaf, O.I., Alotaibi, Y., Alsufyani, A., & Alghamdi, S. (2021). Blockchain Based Crop Insurance: A Decentralized Insurance System for Modernization of Indian Farmers. Sustainability, 13, 8921. https://doi.org/10.3390/su13168921.
Park, A., & Li, H. (2021). The effect of blockchain technology on supply chain sustainability performances. Sustainability, 13(4), 1726. htpp://doi.org/10.3390/su13041726.
Reddy Maddikunta, P. K., Hakak, S., Alazab, M., Bhattacharya, S., Gadekallu, T. R., Khan, W. Z., & Pham, Q.-V. (2021). Unmanned Aerial Vehicles in Smart Agriculture: Applications, Requirements, and Challenges. IEEE Sensors Journal, 21(16), 17608–17619. htpp://doi.org/10.1109/JSEN.2021.3049471.
Said Mohamed, E., Belal, A., Kotb Abd-Elmabod, S., El-Shirbeny, M. A., Gad, A., & Zahran, M. B. (2021). Smart farming for improving agricultural management. The Egyptian Journal of Remote Sensing and Space Science, 24(3), 971-981. htpp://doi.org/10.1016/j.ejrs.2021.08.007.
Schmidt, C. G., & Wagner, S. M. (2019). Blockchain and supply chain relations: A transaction cost theory perspective. Journal of Purchasing and Supply Management, 25(4), 100552. htpp://doi.org/10.1016/j.pursup.2019.100552.
Shoaib-Farooq, M., Riaz, S., Abid, A., Abid, K., & AzharNaeem, M. (2019). A Survey on the Role of IoT in Agriculture for the Implementation of Smart Farming. IEEE Access, 7, 1-10.
htpp://doi.org/10.1109/ACCESS.2019.2949703.
Stindt, D. (2017). A generic planning approach for sustainable supply chain management-How to integrate concepts and methods to address the issues of sustainability?. Journal of cleaner production, 153, 146-163. htpp://doi.org/10.1016/j.jclepro.2017.03.126.
Su, Y., & Wang, X. (2021). Innovation of agricultural economic management in the process of constructing smart agriculture by big data. Sustainable Computing: Informatics and Systems, 31, 100579. htpp://doi.org/10.1016/j.suscom.2021.100579.
Tao, W., Zhao, L., Wang, G., & Liang, R. (2021). Review of the internet of things communication technologies in smart agriculture and challenges. Computers and Electronics in Agriculture, 189, 106352. htpp://doi.org/10.1016/j.compag.2021.106352.
Totin, E., Segnon, A., Schut, M., Affognon, H., Zougmoré, R., Rosenstock, T., & Thornton, P. (2018). Institutional Perspectives of Climate-Smart Agriculture: A Systematic Literature Review. Sustainability, 10(6), 1990. htpp://doi.org/10.3390/su10061990.
Vogel-Heuser, B., Hess, D. (2016). Guest editorial Industry 4.0–prerequisites and visions. IEEE Trans. Autom. Automation Science and Engineering. 13(2), 411–413. htpp://doi.org/10.1109/TASE.2016.2523639.
Walsh, D., Ting-Fung, M., Hon, I., & Zhu, J. (2019). Artificial intelligence and avian influenza: Using machine learning to enhance active surveillance for avian influenza viruses. Transboundary and Emerging Diseases, 66(6), 2537-2545. htpp://doi.org/10.1111/tbed.13318.
Wang, J., Bell, M., Liu, X., & Liu, G. (2020). Machine-Learning Techniques Can Enhance DairyCow Estrus Detection Using Location andAcceleration Data. Animals, 10(7), 1160. htpp://doi.org/10.3390/ani10071160.
Yadav, V. S., Singh, A. R., Raut, R. D., Mangla, S. K., Luthra, S., & Kumar, A. (2022). Exploring the application of Industry 4.0 technologies in the agricultural food supply chain: a systematic literature review. Computers & Industrial Engineering, 169, 108304. htpp://doi.org/10.1016/j.cie.2022.108304.
Zhang, L., Ibiba, K., & Brown, W.L. (2018). Internet of Things applications for agriculture" in Internet of Things A to Z: Technologies and Applications. First Edition. Edited by Qusay F. Hassan. By The Institute of Electrical and Electronics Engineers, Inc. Published 2018 by John Wiley & Sons, Inc. htpp://doi.org/10.1002/9781119456735.
Zhai, Z., Martínez, J.F., Beltran, V., Lucas, N., & Martínez, N.L. (2020). Decision support systems for agriculture 4.0: Survey and challenges. Computers and Electronics in Agriculture, 170, 105256. htpp://doi.org/10.1016/j.compag.2020.105256.
Zhu, Y., Wu, D., & Li, S. (2013). Cloud computing and agricultural development of china: theory and practice. Agricultural and Food Sciences, Computer Science. 10(1) 7-12. htpp://doi.org/10.26438/ijcse/v8i1.159165.