Smart Farming: AI and IoT-Based Solutions for Real-Time Agriculture Monitoring - Kadao Anjali Krushna; Shivaji Ghorpade Bipin (SHS Web of Conferences)
The power of Artificial Intelligence (AI) and the Internet of Things (IoT) contributed to the change of the traditional farming to smart farming systems and major improvements in the agricultural sector. This research investigates an AI and IoT-based solution for real-time agricultural monitoring and management. There is a network of IoT sensors that work in various environments from which data is collected regarding soil moisture, temperature, and humidity among many other parameters. These data streams are analyzed by advanced AI algorithms that generate actionable insights. The basic intention is to minimize costs of irrigation, fertilizer and pest control and to maximize crop yield through minimizing wastage of resources. The machine learning models are used to predict possible points of problems like disease outbreaks or nutrient deficiencies so that appropriate steps can be taken preemptively. Additionally, real time monitoring system has the ability to help farms with precision farming by recommending tailored solutions to farmers through user friendly interfaces on smartphones and other digital devices. Case studies conducted at a variety of different agricultural sites of smallholdings as well as large scale are used to validate the system's effectiveness. The preliminary results suggest that crop productivity as well as the cost efficiency are significantly improved. The AI and IoT technologies combination through this study helps businesses to operate with a sustainable and resilient agricultural framework. Furthermore, it solves some important challenges in contemporary farming of today such as climate change, resource scarcity, and global food insecurity, paving the way to more efficient as well as sustainable agricultural practices.