This use case breaks down a case study by WaterScope Zrt., a company committed to improving the water industry and protecting the environment.
To improve water supply and quality in the region of Tápióság in Hungary, WaterScope Zrt. launched an IoT monitoring system that measures data and monitors water networks in locations where other telecommunications, technology, or energy supply is not available.
The IoT deployment gathers real-time data on the performance of the water distribution network, identify potential leaks, reduces losses and eventually maintains a sustainable and reliable supply of water to meet the demands of the region.
Water production wells and water tower supply require continuous monitoring to ensure that they are functioning optimally. Real-time information about their performance allows operators to make informed decisions about the optimal pressure levels and flow rates needed to maintain a consistent water supply, reduce network load, increase supply security, and improve overall work efficiency.
In addition, real-time data can also be used to identify hidden leaks in the water distribution network. By analyzing flow data, operators can identify areas of the network where water loss is occurring, and take targeted action to reduce losses and increase the efficiency of the system.
This helps conserve precious water resources and supports cost savings for the water utility, as reducing water loss can lead to significant reductions in operational costs over time.
For the required online measurements, WaterScope S2N data acquisition and wireless data transmission devices have been installed to continuously monitor the operation of a waterworks’ pumping station.
The solution measures the pumps’ electrical performance, monitors their operating time and power consumption, measures water pressure, records water meter data, and gives warnings about flooding.
It successfully provides measurement and data collection capabilities without human intervention, even in areas that are not adequately equipped with access and communication infrastructure.
In this use case, a LoRa network is used, that transfers data to the LORIOT Network Management System. A separate LoRa® network was installed for the data collection.
In addition to real-time data collection and transmission, the WaterScope S2N devices are also equipped with alerts and reporting capabilities. This means that the devices can send notifications to the users if any abnormal values are detected, allowing for immediate action to be taken to prevent any potential problems.
The S2N Monitoring System Elements include:
The data presented in the graphs below provides valuable insights into the operation of the wells and the irrigation needs of the area. It appears that the two wells are currently operating in parallel, but the data suggests that alternating their operation may be more efficient. This could potentially save energy and reduce costs.
The second chart indicates that the current pressure may be too high for the needs of the village. Additionally, considering the size and topography of the village, a lower pressure may be more appropriate. Lowering the pressure could result in less waste and more efficient use of resources.
The data presented in the solution is a clear indication of the critical role that well and irrigation systems management play in ensuring the optimal utilization of resources while meeting the community's needs.
In today's world, where resources are limited and the demand for food and water is increasing, it is essential to adopt efficient and sustainable practices to manage our resources effectively.
In conclusion, the resounding success of the solution paved a way for a more efficient and sustainable future.
WaterScope Zrt was founded in 2016, the founders and employees of the company are specialists with extensive experience in the water industry and IoT applications, who are also committed to environmental protection and are at home in product and software development, wireless data collection and communication, system integration, and In AI/BI-powered data analysis.
