Objective

  • IOT is the extension of internet connectivity into physical devices and everyday objects with the aim of monitoring and controlling them.
  • When combined with Machine Learning, NLP and Image Recognition, IOT can act as a powerful bridge between digital and physical worlds.
  • Businesses can employ IOT solutions to monitor and control their business operations from a back-office control room.

Methodology

IOT Solution Design

Identify devices & outcomes to be monitored and controlled.

Sensor, actuator and connectivity design architecture.

This phase involves study of all end-point devices which need to be monitored and controlled. Further, sensors and actuators needed for monitoring and control are identified and connectivity solution architecture is prepared.

IOT Solution Deployment

Install Sensors and Actuators.

Implement connectivity solution including MQTT or similar.

Implement back-end dashboard and alerts mechanism

This phase involves installation of Sensors and Actuators. Connectivity solution including message broker solution such as MQTT Broker is implemented either on in-premise or cloud servers. Dashboard and alerts solution is implemented in the back-office.

Test and Go Live

End-to-end solution testing from end-point devices to back-office.

User Training and Go Live

Plan for predictive analytics solution e.g. breakdown prediction

End to end testing from end-point devices to the back-office is tested for information transmission and accuracy. Users are trained on IOT solution followed by system Go Live. Downstream predictive analytics solutions such as machine breakdown prediction can optionally be conceptualized once the IOT solution goes live.

Deliverables

  • IOT Solution Architecture
  • Implemented IOT solution including sensors, actuators, connectivity solution and back-office dashboard & alerts system.

Case Studies

  • Learn how neurIOT helps an energy company monitor its gas-fired plant in real-time using IOT.
  • Learn how neurIOT has partnered with a Life-Sciences Research company to develop a bio-sensor for semi-paralytic (hemiplegial) patients