Development of a Serverless Energy Analytics Platform for Smart Consumption Optimization

The client faces difficulties in processing and visualizing large volumes of energy consumption data from connected IoT devices. They require a scalable, reliable, and cost-effective solution to deliver interactive dashboards that enable consumers to analyze and optimize their energy usage efficiently, while supporting high user traffic and real-time data streaming.

A mid to large-sized enterprise providing energy management services to commercial and industrial facilities, seeking to enhance energy performance through real-time analytics and visualizations.

• Design and implement a serverless architecture capable of processing high-frequency energy consumption data.
• Create an accessible and interactive dashboard interface for consumers to visualize energy data.
• Ensure high system scalability to handle increasing user load and data volume.
• Reduce operational costs through cloud-native services and optimized data processing workflows.
• Provide reliable data streaming and visualization to facilitate informed energy consumption decisions.

• Serverless data ingestion pipeline leveraging cloud functions or equivalents to collect energy usage data from IoT devices at high frequency.
• Backend data processing layer capable of aggregating and analyzing real-time data streams with scheduled updates.
• Secure data storage solutions optimized for high availability, including managed relational databases and NoSQL clusters.
• Interactive, user-friendly dashboards presenting energy analytics insights with drill-down capabilities.
• Integration with IoT device management systems for seamless data collection and maintenance.
• Scalable architecture designed to support increasing user traffic without performance degradation.

• IoT device data streams for energy consumption data ingestion
• Management APIs for connected devices
• Security and authentication services for user access control

• High scalability to accommodate growing user base and data volume
• Fast data processing and update frequency for real-time visualization
• Robust security measures to protect sensitive energy data
• Cost-effective cloud architecture to minimize operational expenses
• Multi-region deployment capability for disaster recovery and latency reduction

The implemented system aims to deliver a high-performance, scalable energy analytics platform that significantly improves data visualization and accessibility for end-users. Anticipated benefits include reduced operational costs through serverless infrastructure, enhanced decision-making capabilities via interactive dashboards, and improved customer satisfaction with reliable, real-time energy insights, mirroring a potential increase in platform adoption and energy optimization outcomes.