Artificial Intelligence Robotics in Agriculture: See & Spray
Keywords:
artificial intelligence, Smart Agriculture, roboticsAbstract
AI-driven technologies address different challenges faced by the agriculture industry, such as soil health, crop yield, and herbicide resistance. These technologies are emerging to improve the efficiency of agriculture. In this study, we will discuss the role of artificial intelligence in agriculture. These days agricultural robots are a highly valued application of Artificial Intelligence. It is predicted that agricultural robots will be designed and developed to complete different tasks such as spraying herbicides and harvesting crops in the next three to five years. Farmers nowadays are equipped with up-to-date machinery and technology. This will ensure more productivity and profitability. It will help to prove the value of these tools over the long haul. As compared to other industries, the risk is easier to model and predict. The case is different in agriculture as it is impacted by environmental factors. Due to this, the extensive testing and validation of emerging AI applications in agriculture are critical. The agriculture industry will continue to adopt emerging AI in future.
References
Zaman, U. (2022). Imran; Mehmood F; Iqbal, N.; Kim, J.; Ibrahim M. Towards Secure and Intelligent Internet of Health Things: A Survey of Enabling Technologies and Applications. Electronics 2022, 11, 1893.
Mehmood, F., Ullah, I., & Kim, D. Deep Learning Based Object Detection Using OpenCV in Smart Homes.
Mehmood, F., Ullah, I., Ahmad, S., & Kim, D. (2019). Object detection mechanism based on deep learning algorithm using embedded IoT devices for smart home appliances control in CoT. Journal of Ambient Intelligence and Humanized Computing, 1-17.
Ghazal, T. M., Rehman, A. U., Saleem, M., Ahmad, M., Ahmad, S., & Mehmood, F. (2022, February). Intelligent Model to Predict Early Liver Disease using Machine Learning Technique. In 2022 International Conference on Business Analytics for Technology and Security (ICBATS) (pp. 1-5). IEEE.
Mehmood, F., Ahmad, S., & Whangbo, T. K. (2022, February). Object detection based on deep learning techniques in resource-constrained environment for healthcare industry. In 2022 International Conference on Electronics, Information, and Communication (ICEIC) (pp. 1-5). IEEE.
Mehmood, A., Mehmood, F., & Song, W. C. (2019, October). Cloud based E-Prescription management system for healthcare services using IoT devices. In 2019 International Conference on Information and Communication Technology Convergence (ICTC) (pp. 1380-1386). IEEE.
Iqbal, N., Ahmad, S., & Kim, D. H. (2021). Health monitoring system for elderly patients using intelligent task mapping mechanism in closed loop healthcare environment. Symmetry, 13(2), 357.
Ahmad, S., Mehmood, F., Khan, F., & Whangbo, T. K. (2022). Architecting Intelligent Smart Serious Games for Healthcare Applications: A Technical Perspective. Sensors, 22(3), 810.
Gondchawar, N., & Kawitkar, R. S. (2016). IoT based smart agriculture. International Journal of advanced research in Computer and Communication Engineering, 5(6), 838-842
Heble, S., Kumar, A., Prasad, K. V. D., Samirana, S., Rajalakshmi, P., & Desai, U. B. (2018, February). A low power IoT network for smart agriculture. In 2018 IEEE 4th World Forum on Internet of Things (WF-IoT) (pp. 609-614). IEEE.
Rajeswari, S., Suthendran, K., & Rajakumar, K. (2017, June). A smart agricultural model by integrating IoT, mobile and cloud-based big data analytics. In 2017 international conference on intelligent computing and control (I2C2) (pp. 1-5). IEEE.
Roopaei, M., Rad, P., & Choo, K. K. R. (2017). Cloud of things in smart agriculture: Intelligent irrigation monitoring by thermal imaging. IEEE Cloud computing, 4(1), 10-15.
Namani, S., & Gonen, B. (2020, March). Smart agriculture based on IoT and cloud computing. In 2020 3rd International Conference on Information and Computer Technologies (ICICT) (pp. 553-556). IEEE.
Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., & Trichina, E. (2022). Artificial intelligence, robotics, advanced technologies and human resource management: a systematic review. The International Journal of Human Resource Management, 33(6), 1237-1266.
Khaliq, A., Waqas, A., Nisar, Q. A., Haider, S., & Asghar, Z. (2022). Application of AI and robotics in hospitality sector: A resource gain and resource loss perspective. Technology in Society, 68, 101807.
Chostner, B. (2017). See & Spray: the next generation of weed control. Resource Magazine, 24(4), 4-5.
Staff, A. S. A. B. E. (2022). See & Spray TM Select by John Deere. Resource Magazine, 29(3), 7-8.
Downloads
Published
How to Cite
Issue
Section
Categories
License
Articles are licensed under an open access Creative Commons CC BY 4.0 license, meaning that anyone may download and read the paper for free.