Water quality prediction on a Sigfox-compliant IoT device: The road ahead of WaterS

Boccadoro, Pietro; Daniele, Vitanio; Gennaro, Pietro Di; Lofù, Domenico; Tedeschi, Pietro

doi:10.1016/j.adhoc.2021.102749

Cited by 17 publications

(9 citation statements)

References 34 publications

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“…This last point is important to consider because more frequent sampling may be required for other WQM applications. In [116], this work is complemented using the deep learning neural network technique, demonstrating the applicability of data analysis using ML. VOLUME XX, 2023…”

Section: ) Sigfoxmentioning

confidence: 99%

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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Section: ) Sigfoxmentioning

confidence: 99%

Wireless Sensor Networks for Water Quality Monitoring: A Comprehensive Review

López-Ramírez,

Aragón-Zavala

2023

IEEE Access

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“…The data rate provided varies from 20 to 250 kbps. NB-IoT terminals incorporate rechargeable batteries [35].…”

Section: Nb-iotmentioning

confidence: 99%

A Study for Remote Monitoring of Water Points in Mauritania Based on IoT (LoRa) Technology

Abeidi

Kerim

Nanne

2022

IJEEI

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Wetlands in Mauritania contain the most important water sources necessary for the survival of rural communities in the country. In these areas, the main rural activities such as animal husbandry, agriculture, and fishing take place. Lack of water or flooding must be monitored to plan solutions in advance. After a comparative study of IoT wireless technologies, we proposed that LoRa technology is the most suitable for our field of application. However, in certain areas where access to the cellular network is difficult, we propose the addition of satellite communication in the LoRamonitoring system to achieve information collected at any point in the world via the cloud and the Internet. We carried out a practical case for the areas covered by the UMTS (3G) cellular network using devices integrating LoRaWAN to evaluate the performance of this technology. The results show the success of the communication over a distance of 14 km.

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“…Figure 3 depicts the SigFox network's architecture, which is a visualization of these explanations. Essential features to consider for using a SigFox as an LPWAN IoT solution include an uplink message capacity of about 140 per day, each with a payload of 12 and transmission requirements [25]. Below is a brief description of the four basic protocol stacks that are found in SigFox: Hence, the long-range, between 10 to 50 km, communication distance in SigFox is summarized in Table 1.…”

Section: Sigfoxmentioning

confidence: 99%

Low Power Wide Area Network Technologies: Open Problems, Challenges, and Potential Applications

Danladi¹,

Baykara²

2022

RCES

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Nowadays, the number of internet of things (IoT) connected devices continues to increase exponentially. However, the core underlying wireless network technologies that enable IoT devices to achieve such growth and wide applications face numerous challenging deployment requirements such as operating range, power consumption, and cost. Low-power wide-area network (LPWAN) technologies enable long-distance, low-power, and low data transmission at a low cost. These new wireless technologies shape the IoT ecosystem due to their wide applications. This study aims to review the various features and analyze the performances of the leading LPWANs, namely LoRa, SigFox, NB-IoT, and Weightless. Initially, precise descriptions of their underlying technologies and various applications were provided. Then, several challenges facing the LPWANs and potential solutions were outlined. Finally, the study analyzed their performance against several specifications, including frequency range, Bandwidth, Modulation, and so on. The outcome shows that these technologies are more efficient than the short and medium-range IoT technologies, particularly regarding power, range, and cost. The study’s findings are hoped to provide a guide and eliminate LPWAN technology selection issues.

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Water quality prediction on a Sigfox-compliant IoT device: The road ahead of WaterS

Cited by 17 publications

References 34 publications

Wireless Sensor Networks for Water Quality Monitoring: A Comprehensive Review

Wireless Sensor Networks for Water Quality Monitoring: A Comprehensive Review

A Study for Remote Monitoring of Water Points in Mauritania Based on IoT (LoRa) Technology

Low Power Wide Area Network Technologies: Open Problems, Challenges, and Potential Applications

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