Vol.: (0123456789) 1 3 Environ Monit Assess (2023) 195:13 https://doi.org/10.1007/s10661-022-10529-3 Multiparameter optimization system with DCNN in precision agriculture for advanced irrigation planning and scheduling based on soil moisture estimation Parasuraman Kumar · Anandan Udayakumar · Anbarasan Anbarasa Kumar · Kaliaperumal Senthamarai Kannan · Nallaperumal Krishnan Received: 28 February 2022 / Accepted: 1 May 2022 © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022 irrigation for precision agriculture farmers to reduce water consumption used for cultivation and increase production yield by comparing water content dur- ing various stages of plant growth and integrat- ing IoT applications into agriculture. It also opti- mizes the water level for future irrigation decisions to maintain crop growth and water stability. The data must be served and stored in the form of a grid view, according to Apriori and GRU (gated recur- rent unit). Using numerous sensor and parameter modelling methodologies, this system assists in the prediction of irrigation planning based on irriga- tion needs. The predicted parameters include soil moisture, temperature, and humidity. This observed experimental data supports smart irrigation in crop production with a high yield and little water use. DCNN has a 98.5% experimental result accuracy rate and the MSE value is predicted in DCNN 99.25% of the time. Keywords Precision agriculture · Wireless sensor network (WSN) · Internet of Things (IoT) · DCNN · Soil moisture · Soil temperature · Humidity · Smart irrigation · GRU Introduction By installing IoT devices in the field, the agricultural industry is focused on IoT technology to get benefits rapidly and with low investment, making farming Abstract Agriculture is a distinct sector of a coun- try’s economy. In recent years, new patterns have evolved in the agricultural industry. In conjunction with sensor scaling down and precision agriculture, the field of remote sensor networks, such as the wire- less sensor network (WSN), was developed. Its major purpose is to make horticultural operations sim- pler to identify, assess, and manage. This paper uses the proposed DCNN to predict soil moisture and plan P. Kumar · A. Udayakumar (*)  Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Abishekapatti, Tirunelveli, Tamil Nadu 627012, India e-mail: udayakumararivu01@gmail.com P. Kumar  e-mail: kumarcite@gmail.com A. Anbarasa Kumar  School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India e-mail: doctoranbuphd@gmail.com K. Senthamarai Kannan  Department of Statistics, Manonmaniam Sundaranar University, Abishekapatti, Tirunelveli, Tamil Nadu 627012, India e-mail: senkannan2002@gmail.com N. Krishnan  Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Abishekapatti, Tirunelveli, Tamil Nadu 627012, India e-mail: krishnan17563@gmail.com