Open-Source Wireless Cloud-Connected Agricultural Sensor Network

Abstract

Agricultural research involves study of the complex soil–plant–atmosphere–water system, and data relating to this system must be collected under often-harsh outdoor conditions in agricultural environments. Rapid advancements in electronic technologies in the last few decades, as well as more recent widespread proliferation and adoption of electronic sensing and communications, have created many options to address the needs of professional, as well as amateur, researchers. In this study, an agricultural research project was undertaken to collect data and examine the effects of different agronomic practices on yield, with the objectives being to develop a monitoring system to measure soil moisture and temperature conditions in field plots and to upload the data to an internet website. The developed system included sensor nodes consisting of sensors and electronic circuitry to read and transmit sensor data via radio and a cellular gateway to receive node data and forward the data to an internet website via cellular infrastructure. Microcontroller programs were written to control the nodes and gateway, and an internet website was configured to receive and display sensor data. The battery-powered sensor nodes cost $170 each, including electronic circuitry and sensors, and they were operated throughout the cropping season with little maintenance on a single set of batteries. The solar-powered gateway cost $163 to fabricate, plus an additional cost of $2 per month for cellular network access. Wireless and cellular data transmissions were reliable, successfully transferring 95% of sensor data to the internet website. Application of open-source hardware, wireless data transfer, and internet-based data access therefore offers many options and advantages for agricultural sensing and monitoring efforts.

Low cost climate station for smart agriculture applications with photovoltaic energy and wireless communication

“…Although the system is less expensive than comparable commercial systems it can be reduced further by using recycled filament or shredded feed stock following distributed recycling and additive manufacturing methods for the 3-D printed parts [59] , [60] . The majority of the costs, however, are in the sensors themselves, which indicates the greatest potential for cost reductions it to apply the open hardware model [61] to making the sensors themselves [62] , [63] . For example, the electronic boards can be fabricated using open source PCB mills [64] , [65] , [66] .…”

BelBuk System—Smart Logistics for Sustainable City Development in Terms of the Deficit of a Chemical Fertilizers

“…Currently, intelligent agriculture uses advanced technologies from the field of AI. It has been proven that such technologies increase the yields by appropriate assessment of the quality [41][42][43][44][45], and then classification of the yields, which significantly influences the optimization of production [46][47][48][49][50]. The use of intelligent sensors [51][52][53][54][55][56][57] and advanced techniques of artificial intelligence [55,58] enable the planning [59][60][61] and analysis of agricultural production.…”

Forty Years of Increasing Cotton’s Water Productivity and Why the Trend Will Continue

“…Researchers have evaluated the use of electronic monitoring systems for irrigation scheduling under a variety of environmental, cropping, and cultural conditions (Phene et al, 1989;Jones, 2006;Gutiérrez et al, 2013;Haule and Michael, 2014;Soulis et al, 2015;Payero et al, 2017;Fisher et al, 2018Fisher et al, , 2020. Work undertaken explicitly for cotton production has also been reported (Bockhold et al, 2001;Thomson et al, 2002;Bellamy et al, 2009;Leib et al, 2015;O'Shaughnessy et al, 2015;Meeks et al, 2017).…”