Cloud-based IoT Solutions for Enhanced Agricultural Sustainability and Efficiency

Abstract

Agricultural sector has been beset by numerous challenges, such as resource management inefficiencies, susceptibility to climate change, and supply chain opacity. These have necessitated the search for innovative solutions that can increase productivity and sustainability. In recent years, advancements in technology have opened up new horizons for agriculture, with the Internet of Things (IoT) emerging as a key driver of what is being termed the 'digital revolution in farming'. This research delves into the transformative potential of Internet of Things (IoT) devices in modern agriculture, particularly in precision farming, automated irrigation, livestock monitoring, smart greenhouses, predictive analytics for crop diseases, and supply chain efficiency. IoT devices provide a platform for farmers to meticulously monitor the needs of individual plants and refine their farming techniques, consequently optimizing resource utilization and enhancing productivity. By employing sensors to scrutinize variables like soil moisture, plant health, temperature, and humidity, farmers can gain real-time data essential for informed decision-making. Our study also explores the efficacy of IoT devices in automated irrigation systems. These devices manage watering schedules predicated on data from soil moisture sensors, regulating the volume of water delivered to each plant or field, thus diminishing water consumption and ameliorating plant health.

In the domain of livestock monitoring, IoT applications have emerged as valuable tools in tracking health and wellbeing parameters, with systems capable of sending real-time notifications about livestock health, location, and overall welfare. The research also delves into IoT applications within smart greenhouses. These advanced structures leverage IoT technology for automatic climate control and monitoring, significantly reducing manual intervention and resource usage. Further, our study examines the role of machine learning in predictive analytics for crop diseases. Here, algorithms utilize IoT-generated data to predict potential disease and pest infestations, empowering farmers to undertake preventive measures proactively. We scrutinize how IoT can enhance supply chain efficiency. By tracking the supply chain from the farmer to the retailer, IoT applications can assure product freshness, mitigate waste, and equip consumers with transparent information about the source of their food.