In many countries, water quality monitoring is limited due to the high cost of logistics and professional equipment such as multiparametric probes. However, low-cost sensors integrated with the Internet of Things can enable real-time environmental monitoring networks, providing valuable water quality information to the public. To facilitate the widespread adoption of these sensors, it is crucial to identify which sensors can accurately measure key water quality parameters, their manufacturers, and their reliability in different environments. Although there is an increasing body of work utilizing low-cost water quality sensors, many questions remain unanswered. To address this issue, a systematic literature review was conducted to determine which low-cost sensors are being used for remote water quality monitoring. The results show that there are three primary vendors for the sensors used in the selected papers. Most sensors range in price from US$6.9 to US$169.00 but can cost up to US$500.00. While many papers suggest that low-cost sensors are suitable for water quality monitoring, few compare low-cost sensors to reference devices. Therefore, further research is necessary to determine the reliability and accuracy of low-cost sensors compared to professional devices.

https://www.mdpi.com/1424-8220/23/9/4424/pdf?version=1682854798

Low-Cost Water Quality Sensors for IoT: A Systematic Review

The rapid growth of the Internet of Things (IoT) and its applications requires high computational efficiency, low-cost, and low-power solutions for various IoT devices. These include a wide range of microcontrollers that are used to collect, process, and transmit IoT data. ESP32 is a microcontroller with built-in wireless connectivity, suitable for various IoT applications. The ESP32 chip is gaining more popularity, both in academia and in the developer community, supported by a number of software libraries and programming languages. While low- and middle-level languages, such as C/C++ and Rust, are believed to be the most efficient, TinyGo and MicroPython are more developer-friendly low-complexity languages, suitable for beginners and allowing more rapid coding. This paper evaluates the efficiency of the available ESP32 programming languages, namely C/C++, MicroPython, Rust, and TinyGo, by comparing their execution performance. Several popular data and signal processing algorithms were implemented in these languages, and their execution times were compared: Fast Fourier Transform (FFT), Cyclic Redundancy Check (CRC), Secure Hash Algorithm (SHA), Infinite Impulse Response (IIR), and Finite Impulse Response (FIR) filters. The results show that the C/C++ implementations were fastest in most cases, closely followed by TinyGo and Rust, while MicroPython programs were many times slower than implementations in other programming languages. Therefore, the C/C++, TinyGo, and Rust languages are more suitable when execution and response time are the key factors, while Python can be used for less strict system requirements, enabling a faster and less complicated development process.

https://www.mdpi.com/2079-9292/12/1/143/pdf?version=1672837422

Performance Evaluation of C/C++, MicroPython, Rust and TinyGo Programming Languages on ESP32 Microcontroller

The imperative to make energy and resource consumption more sustainable is prompting a critical reconsideration of all human endeavours. Within urban water management, the drive to enhance sustainability is grounded in the recognition that water services consume a substantial amount of energy and that wastewater contains valuable resources, including water, heat, organic matter and essential plant nutrients. To make urban water systems more sustainable, a paradigm shift is needed. Among the proposed strategies, source separation coupled with anaerobic co-digestion appears to be an effective means of recovering energy, water and nutrients. Here, as existing centralized infrastructure that serves tens to hundreds of thousands of people is difficult to alter and the technologies needed to realize this strategy are difficult to implement in single-family homes, we consider the scale of a city block. Using a quantitative model of unit processes that simulate energy, water and nutrient flows, we consider the technical and economic feasibility of a representative decentralized system, as well as its environmental impacts. To realize potential synergies associated with on-site use of the recovered resources, we complement the decentralized water system with vertical farming, photovoltaic energy generation and rainwater harvesting. Our analysis suggests that decentralized water systems can serve as a cornerstone of efforts to enhance resource efficiency and improve the resilience of cities. Decentralized source separation offers a cost-effective, resilient alternative to conventional methods, enhancing resource recovery and reducing environmental impacts.

Using water and wastewater decentralization to enhance the resilience and sustainability of cities

IoT Innovations in Sustainable Water and Wastewater Management and Water Quality Monitoring: A Comprehensive Review of Advancements, Implications, and Future Directions.

An unsupervised method to exploit low-resolution water meter data for detecting end-users with abnormal consumption: employing the DBSCAN and time series complexity

Water supply systems are essential for a modern society. This article presents an overview of the latest research related to information and communication technology systems for water resource monitoring, control and management. The main objective of our review is to show how emerging technologies offer support for smart administration of water infrastructures. The paper covers research results related to smart cities, smart water monitoring, big data, data analysis and decision support. Our evaluation reveals that there are many possible solutions generated through combinations of advanced methods. Emerging technologies open new possibilities for including new functionalities such as social involvement in water resource management. This review offers support for researchers in the area of water monitoring and management to identify useful models and technologies for designing better solutions.

/pdf/advanced-techniques-for-monitoring-and-management-of-urban-1h9l4dov.pdf

Advanced Techniques for Monitoring and Management of Urban Water Infrastructures—An Overview

Water supply infrastructure management has many challenging aspects that include smart infrastructure monitoring, data collection and storage, data analysis and decision support. In this paper we propose a prototype system that comprises solutions for monitoring water consumption, data collection and storage, as well as for data analysis, with the aim of providing support in the form of anomaly notifications and water consumption forecasts for residential consumers information applications.

A Prototype System for Urban Water Consumption Monitoring and Anomaly Detection

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Advanced Techniques for Monitoring and Management of Urban Water Infrastructures—An Overview

A Prototype System for Urban Water Consumption Monitoring and Anomaly Detection