Design and Application of a Low-Cost, Low- Power, LoRa-GSM, IoT Enabled System for Monitoring of Groundwater Resources With Energy Harvesting Integration

Abstract

The rapid expansion of Internet of Things (IoT) devices and applications has accelerated research in various areas of human development. However, the cost of commercial instrumentation impedes the momentum of technological growth in developing regions. In this study, a low-cost, low-power, wireless sensor network for groundwater monitoring (LWNGM) was developed to provide near real-time groundwater level data to support prudent decision making in groundwater resource management in Zanzibar, Tanzania. To facilitate reproducibility, we provided a detailed description of the LWNGM development procedure. The system is based on the ATmega328P microcontroller platform and incorporates low-cost MS5803-14BA and MB280 sensors. To provide a low-power scheme, the Arduino UNO wakes up in six-hour intervals for measurements and data-logging to the SD card, and at twelve-hour intervals for relaying data (in batches) to the LoRa gateway, before it goes back into a deep-sleep mode for the rest of the time (duty cycle<1% ). The average power consumption for the end node across all system cycles was 104.081mW. The power autonomy of all nodes is provided by a 3.7V, 5000mAh rechargeable LiPo battery, and a 9V, 600mAh rechargeable Liion battery, respectively, which are supported by 6V and, 3W solar chargers. The data processing and storage components, as well as the data visualization dashboard, were created using free and open-source software. The LWNGM was reasonably priced, ranging between $350 and $400. The proposed system allows for the adoption of hydrological monitoring, particularly in areas with a limited budget for hydrologic management.

An Efficient LoRa-Enabled Smart Fault Detection and Monitoring Platform for the Power Distribution System Using Self-Powered IoT Devices

“…For the rest of the nodes, a large proportion of the packets sent arrived at the gateway without error and with a packet reception rate greater than 88%. These findings are consistent with the findings of other researchers [67], [96], [97]. This was achieved with a spreading factor of 7, a coding rate of 4/6, and a bandwidth of 125 KHz.…”

A Review of Groundwater Management Models with a Focus on IoT-Based Systems

“…A low-cost, low-powered, IoT enabled approach integrated with energy harvesting groundwater resource monitoring system was designed by Kombo et al [187]. In this study, the authors developed this groundwater monitoring system to produce real-time data to aid decision making in groundwater resource management in Bandamaji station situated at Zanzibar Tanzania.…”

“…MS5803-02BA and NXP MPX5010 DP [190] Not Specified Arduino Pro Mini or Nano Except for the reported cost analysis, the power consumption analysis was not given. Redesigned MS58030-14BA and MBE280 [187] LoRa and GSM Arduino Uno or Mega It requires one or more gateways because the single-channel gateway used limited the number of nodes that can communicate with the LoRa-enabled gateway simultaneously.…”

“…However, the contrary is the case in groundwater-level management [187][188][189][190]. Although there are few application cases, they are synonymous with the use of high power and cost networks; most deployed are commercial pressure transducers without outlining their energy implications, power consumption analysis, or the overall cost implications [187]. Consequently, the use of the Internet of Things based Low-Cost Wireless Sensors Networks (LCSNs) has emerged as an alternative to solve these challenges.…”

“…The application and deployment of low-cost IoT-enabled Wireless Sensors Networks (WSN) technologies in surface water management have gained tremendous progress. However, the contrary is the case in groundwater-level management [187][188][189][190]. Although there are few application cases, they are synonymous with the use of high power and cost networks; most deployed are commercial pressure transducers without outlining their energy implications, power consumption analysis, or the overall cost implications [187].…”