Machine Intelligence, Big Data Analytics, and IoT in Image Processing

8A Status Quo of Machine Learning Algorithms in Smart Agricultural Systems Employing IoT-Based WSN: Trends, Challenges and Futuristic Competences

Abhishek Bhola¹*, Suraj Srivastava², Ajit Noonia³, Bhisham Sharma³ and Sushil Kumar Narang³

¹ Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India

² Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India

³ Chitkara University School of Engineering and Technology, Chitkara University, Himachal Pradesh, India

Abstract

Wireless sensor network (WSN) is widely utilized in real-time practices due to its low cost, large geographical coverage, and easy deployability. The job of WSNs is to monitor a field of interest, collect data, and send it back to the base station for post-processing analysis. This field comprises various challenges, such as selection of network routing strategies due to its dynamic nature, quality of service, decreasing throughput, security, etc. In the recent past, various machine learning approaches are successfully utilized in the field of WSN to overcome the above issues. In smart agriculture, this network is used for monitoring field temperature, measuring soil quality, irrigation systems, crop production, and so on. In this work, the study and discussions about the current trends, various challenges, and their possible machine learning-based solutions for smart agriculture using WSN are presented with their ...