Data-driven technology is taking over the water management business. Whether it's monitoring pipeline and storing tanks or managing irrigation, most organizations require solutions to better grasp water consumption and identify sources of waste.
IoT presents a viable mechanism to bridge the gap between physical systems and real-time information.
What does IoT bring to water management?
Water management IoT systems use connected sensors and devices to gather data from water infrastructure. Sensors could track:
Water pressure
Water flow rate
Consumption
Tank water level
Equipment status
Irrigation needs
Data collected via these sensors could then be transferred to a common hub for monitoring and analysis. Operators would gain the benefit of real-time information over sporadic, human-measured data readings.
- Real-time Monitoring
One of the top benefits IoT offers is its real-time monitoring capability. There may be thousands of pipelines, storage tanks, distribution points and pumps in an existing water system and it could be an enormous task to keep track of them. Sensors attached to critical areas can provide information in real time at various points within the system, assisting organizations in recognizing a deviation in the network. A drastic shift in pressure might suggest the need to investigate a part of the network.
- Detect potential leaks
Water leakage may be a considerable concern and IoT can assist significantly in detecting this waste. A sensor would gather the data regarding the rate of water flow in the system and if an anomalies arise from normal flow rates and conditions, the affected section of the network may be monitored more closely. Early identification of leaks is crucial in reducing water wastage.
- Water consumption
IoT could also help analyze how much water is consumed and at what points. Organizations can determine precisely where in a network most water is being consumed and where demand peaks using the information acquired from all relevant sensors. Certain questions such as the below can be answered with real-time data.
Where is water use highest?
When are demands elevated?
Why is there usage occurring that deviates from normal?
Where can resources be managed in a better fashion?
- Predictive maintenance
Maintenance is a key element that most water systems may have issues tracking. Sensors placed at critical points can aid in monitoring water systems as well as their operation by gathering data on their performance. With appropriate analytics, organizations can forecast equipment failure prior to an issue arising from it. The entire system can switch to scheduled preventative maintenance instead of crisis management when an equipment breakdown occurs.
- Automation
The interconnectedness provided by the IoT can be directly linked to equipment like pumps and valves, as well as irrigation systems to help with automation. Workstations can run certain functions without human assistance once predefined criteria are satisfied from the sensor information obtained. An irrigation system could activate at will based on the detected moisture levels and atmospheric conditions surrounding the vegetation being watered.
Turning IoT to AIoT
Raw data generated from IoT can prove useful but often an interpretation must be made in order to form actionable insights. AI and Machine learning would analyze the vast amounts of data produced by IoT sensors and make sense of it to predict and determine patterns. Artificial Intelligence of Things (AIoT) represents the fusion of IoT and AI and is crucial when you're moving from the realm of simply monitoring equipment to determining its overall implications.
Companies and organizations are now collaborating to utilize AIoT and smart infrastructures for systems that span across infrastructure monitoring, environmental impact and automation.
Aperture Venture Studio can be a notable entity working in this capacity: https://apertureventurestudio.com/
Factors to address when adopting technology
IoT is not a plug-and-play solution and must not be approached in that manner. Organizations would need to have reliable sensors, stable connectivity, cybersecurity precautions, proper data management strategy, ensure compatibility with current infrastructure and have adequate measures for ongoing maintenance. Data quality would significantly determine the value of the analysis derived from it.
Conclusion
With increasingly sophisticated water infrastructures, the IoT will provide organizations with valuable insights into what is transpiring with their networks. Real-time data, leak detection, consumption analytics, predictive maintenance and automation would all contribute toward more robust water management strategies. Beyond simply interconnecting devices, the key lies in being able to translate the information collected by IoT devices into practical and insightful knowledge that assists in critical decision-making and this is why the IoT is essential along with analytics and AI for the future of smart infrastructures.
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