The ability to remote monitor river levels can is possible with IoT technology. IoT allows you to monitor river levels in multiple locations accurately, and the data can be transmitted back wirelessly in real-time. In this blog post, we look at the different components and sensors required to monitor river levels.
Microsoft Azure is a powerful platform on which you can build your IoT application. We look at how Libelium IoT sensors, Azure IoT Hub and PowerBI can be used to monitor air quality in several easy steps. Data such as pH, ORP and temperature are collected, transmitted using 4G then processed and visualised using Microsoft Azure, Azure SQL and PowerBI. Read more
IoT sensors can be used to measure ORP (Oxidation Reduction Potential) in swimming pools, rivers, lakes and drinking water supplies. In this article, we provide an outline of ORP and its relevance in regards to Smart Water applications. When IoT sensors measure ORP, pH and temperature, the data can be transmitted wirelessly to a database server or cloud platform such as Microsoft Azure. Data can then be visualised in dashboards, mobile apps or using applications such as Microsoft Power BI or Tableau. Read more
We regularly speak to customers who have a requirement to measure turbidity levels in water supplies, rivers and other bodies of water. IoT is a powerful and cost-effective way to measure turbidity and transmit the results for analysis, visualisation and reporting.
Turbidity is the loss of transparency, cloudiness or haziness of fluid due to the presence of particles that are invisible to the human eye. These suspended solids cause the water to appear murkier, as the turbidity increases. Smart water solutions and IoT have specialist sensors that can measure turbidity levels.
Smart Water solutions use IoT (Internet of Things) technologies to monitor and measure water quality, conserve water supplies and enable cities to function efficiently. In this article, we outline four examples of how Libelium Plug&Sense can be used for Smart Water applications. The following examples demonstrate several implementations of the technology, and we outline how it can be used to enhance decision making, monitor trends and generate alerts.
