PRoblem statement
Smart Pre-Categorization of potential contaminant upon event occurrence


Smart Pre-Categorization of potential contaminant upon event occurrence
How might we develop a smart pre-categorisation classification algorithm of the type of contaminant present in the water matrix upon event occurrence from the different sensor data provided?
Problem Statement
Background Context

At PUB, to ensure our water supply is running 24/7 sustainably, efficiently and serving our businesses and citizens continuously, we have to ensure our infrastructure and equipment are performing at its intended performance standards.
Mechanical & Electrical (M&E) equipment such as pumps, compressors, air blowers, centrifuges, switchboards, transformers are deployed in areas like water & wastewater treatment plants, pumping stations, reservoirs, etc.
The equipment immediate environment can be categorised as outdoor, indoor and also underground.
They are subjected to high temperature variation, high humidity atmospheric condition, and possible environmental noise such as stray voltage, power surge and lightning transient.
In addition, these field equipment are handling a variety of media, such as raw water, used water, treated water, aeration air and process sludges.
In used water reclamation plants, the media may contain grit, debris and stringy matter, hence causing corrosion/damage to the equipment.
Current Practice & Approach
IOT Sensors – Online Temperature Sensor and Vibration Sensors are currently used to monitor the equipment conditions.
A dashboard platform is used for monitoring and alerts when the equipment health indicators (whose intelligence is derived from the datapoints gather from an IOT sensor tracking a particular equipment) shows a differing status from the baseline norm.
Ideal Solution
A smart pre-categorization of classification algorithm that can help to determine the type of contaminant in the water matrix (eg, organic based, anorganic/ion-based etc) upon an event occurrence.
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Key Evaluation Criteria
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Cost effectiveness against the proposed outcome
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Cost competitiveness against existing solutions