IoT technology for smart Water system

A serious drop in ensuring the water quality in the distribution system is a factor that affects public health. This could lead to increase in biological and non-biological contents, change in colour and odour of the water. These contaminants cause a serious threat to the whole water ecosystem. The conventional methods of analyzing the water quality require much time and labour. So there is a need to monitor and protect the water with a real time water quality monitoring system in order to make active measurements to reduce contamination. The growth of the technology had helped in developing efficient methods to solve many serious issues in real-time. Internet of things (IoT) has achieved a great focus due to its faster processing and intelligence. This paper focuses on discussing the architecture, applications and need of IoT in water management syste

Design of monitoring applications and prediction of key industrial metrics: IIoT + AI

The global industry has suffered deep changes in the last years because of the successful development and integration of new technologies. Industry 4.0 has emerged as a new standard for achieving efficiency and improving processes. Among the technologies used in Industry 4.0, Internet of Things applied to industry (IIoT) enable real-time, intelligent, and autonomous access, collection, analysis, communications, and exchange of process, product and/or service information, within the industrial environment, so as to optimize overall production value. Because of its importance, in this project, a methodology for extracting, analyzing and using the data gathered by IIoT devices is proposed in order to extract meaningful information and to predict industrial key metrics with Artificial Intelligence. In addition, for the complete validation of the proposed methodology, a practical implementation of all the mentioned aspects is carried out by developing a study of the industrial process in the wastewater treatment field using the data collected by an Industrial Internet of Things infrastructure and modelling key time series metrics, such as total organic carbon (TOC) and carbon removal performance (CRP) by using Machine Learning models XGBOOST Regressor, Multi-Layer Perceptron (MLP) Regressor and Support Vector Regressor (SVR) to implement a dashboard with an operational panel and a decision-making panel that helps anticipate possible deviations in the performance of the industrial process

Sistema automático de monitoreo de mercurio en tiempo real en aguas aledañas a explotaciones mineras y petroleras usando una plataforma IOT

El Perú es un país dotado de un vasto número de recursos geológicos que lo convierten, por tanto, en una potencia mundial para la producción minera. Sin embargo, los vertimientos de desechos producidos por la actividad minera y petrolera tienen un impacto grande en el ecosistema ocasionando serios problemas de contaminación ambiental. Estos vertimientos poseen metales pesados tales como mercurio, plomo y cadmio, los cuales son movilizados por las aguas contaminando todo lo que esté a su alrededor alterando tanto la vida humana como la del resto de especies. Por otro lado, la detección tradicional de metales pesados no se realiza en tiempo real, sino que es manual y se lleva a cabo en laboratorios equipados con personal calificado. Entonces una medición en laboratorio, que puede ser realizada días después de haber colectado la muestra, puede no reflejar de manera certera los cambios dinámicos de los contaminantes en el agua. Asimismo, el mercurio es uno de los metales pesados con más impacto contaminante, por ende, su monitoreo es de real importancia para mantener un control más eficiente sobre el modo en que el mercurio está contaminando. Es así que, el presente trabajo plantea un diseño innovador de un sistema de monitoreo en tiempo real de mercurio en aguas aledañas a explotaciones mineras y petroleras usando una plataforma IoT, de modo que los datos obtenidos por los sensores sean enviados a una plataforma en la Nube, permitiendo de esta manera que los entes reguladores puedan tener acceso a estos datos y observar los cambios dinámicos que se producen en la contaminación del agua. Adicionalmente, el diseño mecánico de este sistema le permite operar en un río en la selva, debido a que es una de las zonas más afectadas por contaminación por mercurio; el diseño eléctrico- energético también comprende la autonomía energética del sistema, ya que posee un sistema de panel solar con batería, lo que ofrece versatilidad en el lugar donde se plantea poner en operación al sistema; y además, la comunicación inalámbrica entre los diferentes elementos que comprenden el sistema proporciona buena conectividad para la transmisión de datos. Finalmente, la aplicación del sistema propuesto ayuda a enfrentar de un modo más innovador la problemática de la contaminación de los recursos hídricos ya que fortalece el control y monitoreo del agua, de modo que se puedan tomar mejores y más rápidas decisiones.Tesi

IoT-enabled water distribution systems - a comparative technological review

Water distribution systems are one of the critical infrastructures and major assets of the water utility in a nation. The infrastructure of the distribution systems consists of resources, treatment plants, reservoirs, distribution lines, and consumers. A sustainable water distribution network management has to take care of accessibility, quality, quantity, and reliability of water. As water is becoming a depleting resource for the coming decades, the regulation and accounting of the water in terms of the above four parameters is a critical task. There have been many efforts towards the establishment of a monitoring and controlling framework, capable of automating various stages of the water distribution processes. The current trending technologies such as Information and Communication Technologies (ICT), Internet of Things (IoT), and Artificial Intelligence (AI) have the potential to track this spatially varying network to collect, process, and analyze the water distribution network attributes and events. In this work, we investigate the role and scope of the IoT technologies in different stages of the water distribution systems. Our survey covers the state-of-the-art monitoring and control systems for the water distribution networks, and the status of IoT architectures for water distribution networks. We explore the existing water distribution systems, providing the necessary background information on the current status. This work also presents an IoT Architecture for Intelligent Water Networks - IoTA4IWNet, for real-time monitoring and control of water distribution networks. We believe that to build a robust water distribution network, these components need to be designed and implemented effectively