On the Use of an IoT Integrated System for Water Quality Monitoring and Management in Wastewater Treatment Plants

Abstract

The deteriorating water environment demands new approaches and technologies to achieve sustainable and smart management of urban water systems. Wireless sensor networks represent a promising technology for water quality monitoring and management. The use of wireless sensor networks facilitates the improvement of current centralized systems and traditional manual methods, leading to decentralized smart water quality monitoring systems adaptable to the dynamic and heterogeneous water distribution infrastructure of cities. However, there is a need for a low-cost wireless sensor node solution on the market that enables a cost-effective deployment of this new generation of systems. This paper presents the integration to a wireless sensor network and a preliminary validation in a wastewater treatment plant scenario of a low-cost water quality monitoring device in the close-to-market stage. This device consists of a nitrate and nitrite analyzer based on a novel ion chromatography detection method. The analytical device is integrated using an Internet of Things software platform and tested under real conditions. By doing so, a decentralized smart water quality monitoring system that is conceived and developed for water quality monitoring and management is accomplished. In the presented scenario, such a system allows online near-real-time communication with several devices deployed in multiple water treatment plants and provides preventive and data analytics mechanisms to support decision making. The results obtained comparing laboratory and device measured data demonstrate the reliability of the system and the analytical method implemented in the device.

Smart Urban Water Networks: Solutions, Trends and Challenges

“…Although not aligned to the topic of water distribution network, the last paper on IoT for wastewater treatment plants also provided useful suggestions to the technical and scientific community about the application of wireless sensor networks that can be a promising approach for different fields of urban water management. In [17] was presented a low-cost IoT system for water quality monitoring for wastewater treatment plants at a close-to-market stage. With a novel ion chromatography detection method, they integrated and tested a nitrate and nitrite analyzer under real conditions.…”

Rancang Bangun Sistem Pakar Pemantau Kualitas Air Berbasis IoT Menggunakan Fuzzy Classifier

“…Nilai pembacaan sensor, derajat keanggotaan tiap himpunan fuzzy, dan hasil klasifikasi kualitas air bisa diamati pada Serial Monitor Arduino Mega 2560, seperti ditunjukkan pada Gambar 12. [15], [17] - [19] hanya terbatas pada melakukan pengukuran beberapa parameter kualitas air. Artinya, proses pengambilan kesimpulan kualitas air men jadi proses terpisah yang melibatkan manusia.…”

“…Pada pengolahan air limbah, IoT telah d iintegrasikan untuk memantau kualitas air limbah. Data sensor dari beberapa pabrik pengolahan air limbah diolah untuk mendukung pengambilan keputusan [17]. Mekan isme pelaporan data kualitas air telah direalisasikan menggunakan IoT pada konfigurasi wireless sensor network .…”

IoT Based Real-Time Monitoring of Phytoremediation of Wastewater using the Mathematical Model Implemented on the Embedded Systems

“…Integration of Wireless Sensor Network (WSN) and IoT was proposed in [24] to perform a Decentralized Smart Water Quality Monitoring System. The sensor device employed a cost-effective optical sensor based-on an ion chromatography system [25] to detect nitrite and nitrate in the water.…”

“…Second, compared to the existing real-time monitoring in phytoremediation [13,14], our approach offers a simple hardware configuration and adopts a recent IoT technology. Third, compared to the existing WWTP monitoring systems [15][16][17][18][19][20][21][22][23][24][25][26][27][28], our approach offers an efficient tool to monitor and examine the phytoremediation models by integrating the IoT platform and the mathematical model, which is implemented on the embedded hardware.…”