Problem Statement
Modern agriculture can benefit significantly from the integration of Internet of Things
(IoT) sensors and artificial intelligence (AI). There is a need for a comprehensive system
that combines these technologies to monitor and optimize various agricultural
processes, including crop health, irrigation, and pest control.
Abstract
This project focuses on the development of a Smart Agriculture system that leverages
IoT sensors and AI algorithms. The system will monitor crucial factors such as soil
moisture, temperature, and pest activity in real-time. AI algorithms will analyze the
collected data to provide farmers with actionable insights, enabling them to make
informed decisions about irrigation scheduling, pest control strategies, and overall crop
management. The project aims to enhance the efficiency and sustainability of
agricultural practices.
Outcome
● Implementation of a Smart Agriculture system with integrated IoT sensors.
● Real-time monitoring and analysis of agricultural parameters using AI algorithms.
● Improved crop yield, resource efficiency, and overall sustainability in agriculture.
Reference
Smart agriculture techniques have recently seen widespread interest by farmers. This is driven by several factors, which include the widespread availability of economically-priced, low-powered Internet of Things (IoT) based wireless sensors to remotely monitor and report conditions of the field, climate, and crops. This enables efficient management of resources like minimizing water requirements for irrigation and minimizing the use of toxic pesticides. Furthermore, the recent boom in Artificial Intelligence can enable farmers to deploy autonomous farming machinery and make better predictions of the future based on present and past conditions to minimize crop diseases and pest infestation. Together these two enabling technologies have revolutionized conventional agriculture practices. This survey paper provides: (a) A detailed tutorial on the available advancements in the field of smart agriculture systems through IoT technologies and AI techniques; (b) A critical review of these two available technologies and challenges in their widespread deployment; and (c) An in-depth discussion about the future trends including both technological and social, when smart agriculture systems will be widely adopted by the farmers globally.
- Programme Water and Jobs the United Nations World Water Development Report, 2016.
- M. S. Farooq, S. Riaz, A. Abid, K. Abid, and M. A. Naeem, “A survey on the role of IoT in agriculture for the implementation of smart farming,” IEEE Access, vol. 7, pp. 156237-156271, 2019.
- M. Ayaz, M. Ammad-Uddin, Z. Sharif, A. Mansour, and E. M. Aggoune, “Internet-of-Things (IoT)-based smart agriculture: Toward making the fields talk,” IEEE Access, vol. 7, pp. 129551-129583, 2019.
- R.-A. Li, X. Sha, and K. Lin, “Smart greenhouse: A real-time mobile intelligent monitoring system based on WSN,” Proc. Int. Wireless Commun. Mobile Comput. Conf. (IWCMC), pp. 1152-1156, Aug. 2014.
- R. Nalwade and T. Mote, “Hydroponics farming,” Proc. Int. Conf. Trends Electron. Informat. (ICEI), pp. 645-650, May 2017.
https://ieeexplore.ieee.org/document/9716089/