K Electric Poles
K Sensors
0 GB/ Data
% Dollars Saved
mn+ Electric Poles

Custom Energy Management Software

Client Overview

The Client is a Microgrid developer Company which aims at creating a sustainable and economic ecosystem for developing micro-grids. Rising Energy prices are a major deterrent to developing economic microgrids. They were looking for an Energy Management System that can lower Energy Prices. Energy saving solutions have become a necessity due to growing carbon footprint and greenhouse gas emissions.As a pilot project, the client entrusted us with a Big Data Analytics solution for a specific area comprising of 2 Lakh LED lights. The aim was to find ways to save energy and monitor energy usage made by these light poles and also some ATM counters in the same vicinity. By leveraging the crucial information collected from this cloud-based analytical solution, the company will be able to reduce power wastage.

Business Solution

To help combat this problem we developed a Big Data Analytics Solution. To collect data each of these 2 Lakh poles are fitted with four sensors each, and these sensors send 168-bitstreams. All put together these sensors are sending 8-10 GB of data every day, regarding power consumption. This string from server store needs to be transferred to the Database to be analyzed.

We further break the string into our format and need to pass this string to calculate which energy unit is working unnecessarily. All this energy data once stored and collected on the Hadoop Data Storage is processed to conduct 250 jobs per day. Each job takes about 2-5 hours which saves time considerably.

This Big Data Analytics platform provides the client with:

Real-Time Analytics

Light units that are functioning during the day causing energy wastage.

Air Conditioning Units running inside ATM counters beyond necessary hours.

Predictive Analytics

Which light units will need to be replaced in near future.

Which light units will consume more electricity than others.

Based on the sustainability reports and result of this Analytics, this web-based Solution helped the facilities managers. They could take required actions to Reduce Energy Consumption, improve key performance and energy efficiency.


The client had the following benefits from the above solution. They are now planning to implement it over a larger geography.

In just one year the client could save 25-30% Energy.

10mn was saved regarding Energy

Reduce Costs overhead for the client by 9.48%


Hadoop Hdfs

Apache Spark

Google Cloud

Hadoop Hive