Exploring the role of machine learning and blockchain in the context of IoT

IoT-enabled development of a smart agriculture framework by combining blockchain technology with machine learning is a new revolution. This combination aims to enhance security in the IoT-based agriculture framework. Machine learning for a smart agriculture framework in the context of IoT can be used in precision agriculture, crop recommendation systems, water and waste management, livestock monitoring, farm management, pest management, and predictive analytics to predict suitable weather conditions for efficient crop management using specific sets of sensors like soil moisture, pH, rainfall detector, temperature sensor, and crop disease detection. Blockchain in the context of IoT can be used in secure data transmission, supply chain management, and smart contract systems based on predefined conditions. In this chapter, we will present a comparative analysis of different machine learning techniques to optimize irrigation, water harvesting, and soil parameters. There are various machine learning models like Support Vector Machine, Convolutional Neural Network, Long Short-Term Memory, Genetic Algorithm, Regression Algorithm, Decision Trees, Random Forest, Clustering, K-Nearest Neighbors, and Gaussian Naïve Bayes for the analysis of various agricultural threats in blockchain and IoT-enabled smart agriculture framework (IESAF). Through a critical examination, this chapter focused on providing the IESAF using the integration of blockchain and machine learning techniques. We will discuss the integration challenges like security, scalability, and interoperability to provide sustainable, more efficient, and favorable conditions for precision agriculture. Also, we will mention future research directions with reference to smart agriculture. At the end of this chapter, we will discuss a case study related to smart agriculture with an opinion to increase productivity through the proposed system. Our proposed framework assists farmers in finding the optimal solution that results in increased crop growth.