Big Picture
How does it work?
Sensor raw data is sampled continuously, containing energy information, from electric, gas, and/or water.
Data is processed and transformed by intelligent edge logger into max, min, ave values; certain KPI are derived.
Transformed data is further categorized, aggregated, and analyzed in the cloud.
Dashboards, Analytics, Alerts, Reports are provided to the customer.
IoT Devices and Edge Logger
All existing smart meters and PLCs with open communication protocols are supported.
Our intelligent edge processing logger can run on both Linux and Windows. Logger runs on-premise near the sensors.
Our flexible architecture enables easy integration of new IoT devices to our system and their data used in the platform.
Transforming the Data
Part of transforming the data is essentially the process of mapping physical context to the data collected based on your facility's structure.
What am I looking at?” the sensor data is organized to fit your facilities. Examples, building 1, building 2, floor 1, floor 2, basement, hvac1, hvac2 etc. You can associated your visible data with your facility and equipment.
You have the flexibility to label your environment in a logical and easy to understand approach while keeping the sensor information.
Measurements and Values
Among other measurements, smart meters sensors capture:
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Current,
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Voltage LL,
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Voltage LN,
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Power (Active, Reactive, Apparent),
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Power Factor,
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Harmonic Distortions
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Weather temperature
Application KPI Values provided:
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Maximum demand
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Base Load
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Duration of time in operation
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Power Factor analysis
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Voltage THD analysis
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Value distribution of a measurement
Quality and Reliability
We use an Agile development methodology.
We use kanban for tracking our features, bug fixes, and improvements that are managed in the form of tickets in Jira.
We use Jenkins to build the docker images and ship them to the IBM docker registry.
We use a CI/CD methodology.