The Next Generation of Smart Meters Using Self-Learning Models

The global market for smart meters, including water, gas, heat, and electricity, is expected to reach $20 billion in 2022. However, many factors are contributing to the increasing difficulty of building reliable smart meter systems. These include an outdated smart meter infrastructure, fast urbanisation, and rising costs for testing and developing these devices, among others. Smart meter systems must fulfill complex regulations, operate in harsh climate conditions while also reducing non-revenue water losses, as well as fulfilling a carbon-neutral and sustainable future under mounting time-to-market pressure while increasing product performance.

Dragging sliders help engineers to generate new ideas and make quick design choices.

New regulations that define metering accuracy, flow rates, valve, and metering technology require stringent calibration and regulatory tests. For a test engineer working on smart meters, Self-Learning models can be the key to success for leveraging existing and new engineering data, while not relying on expensive, time-intensive, and repetitive tests.

Ensuring accurate measurement of gas usage has widespread benefits: smart meter engineers can track and predict their own expenditure, while suppliers can understand their client base and provide a more reliable and bespoke service.

Monolith is a no-code application that offers engineers a new way of leveraging their smart meter test data to help them explore, understand and predict performance, thereby reducing test times by up to 70%. Additionally, Monolith offers collaboration features to ensure institutional knowledge is capitalised on, shared, and documented for generations to come.

 

The Next Generation of Smart Meters

When designing the next generation of smart meters, it is important to keep several key factors in mind. With higher reliability, utilities spend less on maintaining existing infrastructure and reduce overall operating costs. A lower power consumption ensures that meters can operate longer on a single battery and with smaller smart meter size, more sensors can be placed in more locations further increasing the “intelligence” and efficiency of the 'grid'—whether water, gas, heat, or electricity. 

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