Decision Makers, Ltd. supplies the following services:
The customer supplies historical water quality data (including abnormal events).
Decision Makers will supply a report that focuses on the question of how long before, and using which measurements and setups, such events may be detected. The report will also estimate the amount of false positives and false negatives generated by such a setup.
The customer supplies historical data files of water quality (without abnormal events).
Decision Makers will supply a report that presents water quality measurement statistics. This includes recommendations for low and high limits for the SCADA system, limits for rate of change monitoring, correlations between major variables, and prediction functions for key parameters.
The customer supplies historical data files of water quality (with or without abnormal events) from several monitoring stations and the water network's basic topology.
Decision Makers will supply a report that shows the relative efficiency of each monitoring station and the optimal combination of sensors.
Based on the Mindset-Suite (EDS, WebApp and Field Monitoring), Decision Makers supplies a cloud-based water monitoring service. Decision Makers will train the water utility staff to use the software. All building and tuning of models is carried out by Decision Makers. Periodic meetings will take place between the DM team and the water utilities staff, in order to review reports, engage in Q&A, and acquire a deep understanding of the water utilities' water data.
Using the Mindset-Predictor tool, Decision Makers provides a prediction about the energy production of photo-voltaic systems. This prediction is made one day ahead (of what) and is based on machine learning algorithms that utilize the Regression Tree algorithm in a unique implementation for time series models. The algorithm uses both the historical data of each inverter and the relevant weather conditions such as temperature, humidity, wind speed, barometric pressure, and cloud coverage.
Using a clustering-based prediction, Decision Makers provides a fault detection service for photo voltaic systems. For each measured output of the inverter, the system builds a profile based on historical data. When the actual value of the output deviates from its profile, it is an indication of a pending problem.