Overview
A global energy services company collaborates with large facilities to utilize IoT sensors and track energy usage. As data volumes grew, their systems struggled to provide timely insights. They partnered with Krish Services to build an Azure-based analytics platform that turned sensor data into clear signals, enabling early action, lower costs, and better energy efficiency.
Client Background
The client is a global provider of smart energy services for industrial customers. They deploy sensors across buildings and equipment to track energy usage, improve performance, and support sustainability goals. Their focus is on helping organizations lower energy costs, reduce waste, and operate more efficiently across large, distributed environments.
Challenges
- Disconnected IoT Data Sources: Unreliable analysis and a lack of a trusted operational view due to sensor data arriving in different formats across sites.
- Delayed Real-Time Monitoring: Delayed visibility into energy spikes and device failures due to batch processing, causing higher costs, slower responses, and missed efficiency opportunities daily.
- Inability to Scale Data Processing: Legacy infrastructure could not handle growing IoT data volumes, restricting expansion, increasing risk, and limiting future analytics capabilities for the business.
Solutions
- Centralized IoT Data Platform: Built an Azure data lake with Databricks to ingest, clean, and analyze sensor data, enabling reliable anomaly detection at scale.
- Real-Time Operational Dashboards: Delivered Power BI dashboards showing live energy metrics across sites, helping teams spot issues faster and act quickly and confidently.
- Scalable Streaming Architecture: Designed a scalable Azure architecture to process millions of records daily, supporting alerts, growth, and future sensor expansion reliably and securely.
Technology in Use
Azure Data Lake
Azure Databricks
Azure Synapse Analytics
Azure Event Hub
Power BI
Business Value Propositions
- Predictive Maintenance Enablement: Early anomaly detection helped teams address equipment issues before failures, reducing unplanned outages and maintenance surprises.
- Lower Energy Waste and Downtime: Real-time monitoring reduced energy spikes and downtime, improving operational efficiency and controlling ongoing operational costs.
- Sustainability Visibility: Clear dashboards gave leaders visibility into energy usage patterns, supporting sustainability targets and carbon reduction initiatives.
- Future-Ready Data Platform: A flexible architecture allows easy onboarding of new sensors without redesigning systems or disrupting operations.
Final Perspective
We unified IoT data on Azure, enabling predictive maintenance and energy savings today, while preparing scalable analytics that will improve sustainability, reliability, and faster decision-making across future operations globally.