Green Leaf Airconditioning Services

remote monitoring

With IoT and M2M technologies, your HVAC plants are brought to your screen, in real time – now you know what’s happening with your chillers at all times, check on historical data and charted trends

artificial intelligence

Machine Learning, using CNN and Deep Learning, is the powerful technology enabler to predict faults, reduce downtime and expensive repairs, and optimize energy efficiency of your chillers

service ERP

Real time data from the HVAC plant, analysed by the AI algorithms, seamlessly translates to actionable intelligence in terms of work instructions and spare parts required, in the hands of our technician

digital @GL

actionable intelligence

for fault prediction

IoT and M2M

As part of our AMC, we install our IoT (Internet of Things) based M2M (Machine to Machine) solution for reading the real time data of your chillers at site. This information is available to you through our user-friendly interface, for operating parameters, trends, alarm and alert history, at a chiller level, and for the entire plant.


  • Asset Monitoring
  • Performance History
  • KPIs on service quality
  • Trend charts
  • Analytics for fault prediction
  • Analytics for energy consumption

machine learning

Data collated through the IoT based remote monitoring system is “washed” through our proprietary Machine Learning algorithms, using CNN and Deep Learning for Expert Systems. This maps monitored data to Expert System correlations, to predict faults in the chillers. The AI system has a parallel application: energy saving through “continuous commissioning”, to operate your chiller plant as real-time responsive to the heat load in your building.


  • Fault Prediction
  • Avoiding costly major repairs
  • Reduce chiller downtime
  • Energy savings

actionable intelligence

Fault predictions from AI algorithms are converted to “actionable intelligence” in the form of work instructions and spare parts requirement for our site technicians. The service ERP translates these fault predictions to job tickets, assigned to technician’s schedule based on fault severity. Corrective work done by technicians at site is logged in the system, along with real-time monitored data to confirm problem resolution.


  • Pre-defined work instructions
  • Faster resolution time
  • First-time-right work by technicians
  • Monitor job progress on the go
  • Predicitve problem solving

points monitored per day
& counting


HVAC equipment.


buildings covered with
remote monitoring


Learn more


Learn more