An AI inspired technology Optimal Intelligent Reporting® searches and finds anomalies in energy consumption and then generates a list of likely reasons why, pointing the user straight at the solution to the anomaly.
Optimal Intelligent Reporting® has been designed to work in built spaces where there is no specific unit of throughput e.g. passengers or production and where energy demand is generated by people performing the usual range of random activities.
Optimal Intelligent Reporting® builds upon existing analytic tools like Exception Reporting where users only need to manage exceptions to the trend average rather than the entire gamut of energy consumption drivers.
To generate ever more reliable solution options to the unstructured query of ‘why is my demand outside of the expected value for the time of day/day of week’ ideally monitoring of at least three utilities with water always included is desirable – water is the best indicator of when a building is occupied.
The continuous learning that the system seeks to achieve is generated by users completing a simple exit screen to every solution/anomaly, identifying which of the generated solutions was correct, or in the event that the correct solution was none of these, entering what is was, which then goes into the system’s knowledge base. In later instances this will be replaced by machine learning.