IoT Based Secure Data Sharing for Precision Agriculture with Optimal Clustering and Hybrid Encryption Algorithm

Sensor nodes in precision agriculture may send secure data. The primary issues for this project are energy efficiency and data privacy. This system employs data clustering, which involves sensor nodes organizing into clusters under the supervision of a cluster head (CH). The <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{C H}$</tex> oversees the other CHs and the cluster's data sharing. Several objective criteria, such as energy, delay, execution time, distance, and residual energy, are considered for determining the optimal <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{C H}$</tex>. The proposed hybrid optimization models will be formed by hypothetically integrating both the conventional Pufferfish Optimization Algorithm (POA) and Reptile Search Algorithm (RSA). When more than one node meets the necessary requirements, this hybrid approach can be used to choose. This hybrid approach is helpful in choosing the best CH for communication when there are numerous nodes that meet the necessary requirements. After the best <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{C H}$</tex> has been chosen, the data must be encrypted before being sent. A cutting-edge hybrid cryptographic technique that combines Blowfish symmetric key encryption with Elliptic Curve cryptography to secure data while maintaining trust and privacy. By choosing the best way, the path selection technique based on self-improved Bald Eagle Search optimization reduces interception and ensures the safe transmission of encrypted data. This thorough research, which focuses on data security and energy saving, gives farmers trustworthy and safe information to help them make more informed agricultural decisions.