Design and Analysis Performance of IoT-Based Water Quality Monitoring System 
using LoRa Technology

Promput, Sommart; Maithomklang, Somkiat; Panya-isara, Chawalit

doi:10.18421/tem121-04

Cited by 12 publications

(14 citation statements)

References 17 publications

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“…LoRa devices have a range of up to 15 kms and use two keys for authentication; however, their data transmission rate is low at 50 Kbps [152,153]. Several groups have carried out research in aquatic environments using these technologies to investigate various parameters [154][155][156][157]. Jen-Yung et al designed a system for monitoring several water parameters using sensors integrated into the ESP-WROOM-32 Wi-Fi module [158].…”

Section: Wireless Sensor Network For Water Quality Sensingmentioning

confidence: 99%

Integrating Wireless Remote Sensing and Sensors for Monitoring Pesticide Pollution in Surface and Groundwater

Mutunga,

Sinanovic,

Harrison

2024

Sensors

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Water constitutes an indispensable resource crucial for the sustenance of humanity, as it plays an integral role in various sectors such as agriculture, industrial processes, and domestic consumption. Even though water covers 71% of the global land surface, governments have been grappling with the challenge of ensuring the provision of safe water for domestic use. A contributing factor to this situation is the persistent contamination of available water sources rendering them unfit for human consumption. A common contaminant, pesticides are not frequently tested for despite their serious effects on biodiversity. Pesticide determination in water quality assessment is a challenging task because the procedures involved in the extraction and detection are complex. This reduces their popularity in many monitoring campaigns despite their harmful effects. If the existing methods of pesticide analysis are adapted by leveraging new technologies, then information concerning their presence in water ecosystems can be exposed. Furthermore, beyond the advantages conferred by the integration of wireless sensor networks (WSNs), the Internet of Things (IoT), Machine Learning (ML), and big data analytics, a notable outcome is the attainment of a heightened degree of granularity in the information of water ecosystems. This paper discusses methods of pesticide detection in water, emphasizing the possible use of electrochemical sensors, biosensors, and paper-based sensors in wireless sensing. It also explores the application of WSNs in water, the IoT, computing models, ML, and big data analytics, and their potential for integration as technologies useful for pesticide monitoring in water.

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Section: Wireless Sensor Network For Water Quality Sensingmentioning

confidence: 99%

Integrating Wireless Remote Sensing and Sensors for Monitoring Pesticide Pollution in Surface and Groundwater

Mutunga,

Sinanovic,

Harrison

2024

Sensors

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“…Advancements have been made in the TMIS approach, introducing novel ways to perform sampling. In [18], a smart boat is employed to enable the collection of samples over long distances using LoRa wireless technology, albeit still requiring direct interaction between the human operator and the sampling tool.…”

Section: A Traditional Manual Lab-based and In-situ Approachesmentioning

confidence: 99%

“…Novel and important implementations that use this technology have been documented in [18], [32], [62], [109], [110]. In [109], the deployment of three LoRa sensor nodes at different distances from the LoRa gateway for the acquisition of parameters such as pH, turbidity, temperature, conductivity, and dissolved oxygen is reported, using the ESP32-LoRa32 transmitter to emit the signal in the 920-923 MHz band.…”

Section: ) Lorawanmentioning

confidence: 99%

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Wireless Sensor Networks for Water Quality Monitoring: A Comprehensive Review

López-Ramírez,

Aragón-Zavala

2023

IEEE Access

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This comprehensive review examines the use of Wireless Sensor Networks as a solution for addressing water quality monitoring and data scarcity. It compares Wireless Sensor Networks with traditional laboratory-based and in-situ monitoring methods, highlighting their superior respons e speed, cost-effectiveness, ease of deployment, and reliable measurements. The paper provides an overview of wireless sensor node architecture, discussing subsystems, Quality of Service requirements, and the significance of low power consumption in microcontroller units. Network solutions for short, medium, and long-range applications are explored, highlighting that Low-Power Wide Area Network is the most effective option for water quality monitoring. Furthermore, the review acknowledges the potential of machine learning techniques within Wireless Sensor Networks for Water Quality Monitoring, highlighting their versatility. A case study analysis of three LPWAN applications is presented, discussing their key characteristics, potential benefits, and important considerations for future implementations. By consolidating current knowledge, this review emphasizes the capacity of Wireless Sensor Networks to overcome data scarcity challenges in water quality monitoring. Valuable insights are provided for researchers, practitioners, and decision-makers seeking to leverage Wireless Sensor Networks, LPWAN technologies, and machine learning techniques for efficient and cost -effective global water quality monitoring.

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“…The LoRa gateways act as bridges between the LoRa nodes and the Internet, receiving data from the nodes and forwarding them to a cloud-based server or an IoT platform [46]- [50]. Several researchers have implemented LoRa such as monitoring health [51]- [54], electrical [55]- [61], water quality [62]- [68] and coal mine [69]- [71]. This paper will present monitoring of DC motors using LoRa and IOT.…”

Section: Introductionmentioning

confidence: 99%

Monitoring DC Motor Based On LoRa and IOT

Suhermanto,

Aribowo,

Shehadeh

et al. 2024

Journal of Robotics and Control

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Electrical energy efficiency is a dynamic in itself that continues to be driven by electrical energy providers. In this work, long-range (LoRa) technology is used to monitor DC motors. In the modern world, IoT is becoming increasingly prevalent. Embedded systems are now widely used in daily life. More can be done remotely in terms of control and monitoring. LoRa is a new technology discovered and developing rapidly. LoRa technology addresses the need for battery-operated embedded devices. LoRa technology is a long-range, low-power technology. In this investigation, a LoRa transmitter and a LoRa receiver were employed. This study employed a range of cases to test the LoRa device. In the first instance, there are no barriers, whereas there are in the second instance. The results of the two trials showed that the LoRa transmitter and receiver had successful communication. In this study, the room temperature is used to control DC motors. So that the DC motor's speed adjusts to fluctuations in the room's temperature. Additionally, measuring tools and the sensors utilised in this investigation were contrasted. The encoder sensor and the INA 219 sensor were the two measured sensors employed in this study. According to the findings of the experiment, the tool was functioning properly.

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Design and Analysis Performance of IoT-Based Water Quality Monitoring System using LoRa Technology

Cited by 12 publications

References 17 publications

Integrating Wireless Remote Sensing and Sensors for Monitoring Pesticide Pollution in Surface and Groundwater

Integrating Wireless Remote Sensing and Sensors for Monitoring Pesticide Pollution in Surface and Groundwater

Wireless Sensor Networks for Water Quality Monitoring: A Comprehensive Review

Monitoring DC Motor Based On LoRa and IOT

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