Future Prospects of Agriculture Using IoT and Machine Learning

Agriculture balances both the world's food supply and the raw resources required by numerous businesses. The combination of Internet of Things (IoT) and Machine Learning (ML) technologies has revolutionized the agriculture industry, enabling efficient and data-driven decision-making processes. This paper explores the future prospects of using IoT and ML in agriculture, highlighting their potential applications, benefits, and challenges. It examines how IoT devices, such as sensors, drones, and smart irrigation systems, can collect present data on soil situations, weather patterns, crop condition, and resource utilization. ML algorithms can then analyze this data to provide actionable insights for optimizing agricultural practices, improving crop yield, and reducing resource wastage. The paper discusses emerging trends, such as precision agriculture (PA), smart farming, and autonomous farming, which leverage the combined power of IoT and ML. It also addresses the challenges of data security, privacy, and scalability associated with implementing IoT and ML in agriculture. By understanding the future prospects of IoT and ML in agriculture, stakeholders in the agricultural sector can harness these technologies to enhance productivity, sustainability, and profitability.