MEMS and Artificial Intelligence Technology for Smart Agriculture

Abstract

The integration of Micro-Electro-Mechanical Systems (MEMS) and Artificial Intelligence (AI) has become a disruptive approach in the design of smart agriculture systems. In this paper we investigate the combined utilisation of MEMS based sensing technologies and AI driven analytical models to improve the productivity, efficiency and sustainability of agriculture. Sensors MEMS sensors are vital in collecting real-time data on the environment and soil conditions, including temperature, humidity, soil moisture, nutrient levels, and crop health status. The collected data is further processed using AI techniques such as machine learning, predictive analytics and intelligent decision-making algorithms to support precision farming practices. With the integration, farmers can closely monitor the conditions of their fields, automate irrigation systems, detect diseases in the early stages and optimise the use of fertilisers and pesticides, which leads to a reduction in operational costs and environmental impact. Moreover, the paper covers recent technological advancements, practical applications, and case studies showcasing the efficacy of MEMS and AI in contemporary agriculture. The challenges like high implementation cost, data security, energy efficiency and technical limitations are also discussed. The study concludes that the integration of MEMS and AI technologies hold great promise for enhancing food production, resource management and sustainable agricultural development. Future research directions include the development of low-cost smart sensors, edge computing and IoT-enabled intelligent farming system for large-scale agricultural applications.