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How we can achieve this?

Due to industrial demand on todays technology, we would like to enhance our product by developing system that can be:

Monitor
Analyze
Make decision making

The route shows stages by stage in order to reach a smart PFCS. Starting from the integrated control system, a device namely PQM 1000s will transmits data for the next stage of IoT process.

Integrated Control System

“PGM”

Stage 1

Raspberry Pi

“Raspberry

Internet of Things (IoT)

“internet

Python/ JavaScript

“coding”

Stage 2

Artificial Intelligence (Ai)

“artificial

Stage 3

Data Monitoring

Our system can extract data from the device installed on PFCS to monitor the movement of real-time data.

  • Active Power
  • Reactive Power
  • Apparent Power (kVA)
  • Power Factor
  • Averange Power Factor
  • Voltage (Volts)
  • Current (Amps)

Data Analysis

Save in Bills

Realise how much bills are saved

Carbon Emission

Observe how much reduction in kVar after PFCS installation.

Clean Energy

Analyse how much clean and efficient energy being distributed on grid

Decision Making

Based on evaluation made by PFCS, it can decide on available information and considering potential outcomes

Machine Learning

Machine learning is a part of AI process embedded into non-living things before it makes a decision. In our next project, we initiate an idea to AI-ing our PFCS as below

IoT Centre (In Progress)