Centralized Digital Energy Metering for Endpoint Control
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Solution Overview
Problem
Conventional energy metering systems are limited in their ability to track individual endpoint energy consumption, leading to inefficiencies in power management and increased costs due to the need for multiple memory units and lack of scalability.
Innovation Solution
A centralized system that uses data collecting devices, sensors, and microcontroller units to monitor and control power consumption across multiple endpoints, processing data for storage in a database and enabling remote control through web or mobile applications, utilizing wireless and wired networks to communicate with a cloud server for optimized power management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional energy metering systems are used, then overall energy consumption can be recorded, but individual endpoint consumption cannot be tracked
Solution Approach 1:
The system segments energy monitoring into two distinct components: a simple data collection unit at each endpoint that only measures and transmits consumption data, and a centralized server that performs all processing, analysis, and storage. This segmentation allows individual endpoint tracking without requiring complex intelligence at each device.
Solution Approach 2:
The centralized server acts as an intermediary that receives raw data from multiple simple endpoint devices, processes the information, and generates comprehensive energy consumption reports. This intermediary approach enables detailed tracking without distributing complexity across the network.
2Loss of information
If multiple memory units are deployed at individual endpoints, then individual consumption can be recorded, but cost and maintainability increase
Solution Approach 1:
The patent extracts the memory and processing functions from individual endpoint devices and consolidates them into a centralized server. Each endpoint only retains minimal data collection capability, while the server handles storage, analysis, and reporting, significantly reducing per-device cost and complexity.
Solution Approach 2:
Multiple data collection units are merged into a single centralized server infrastructure for processing and storage. This consolidation allows the system to serve multiple endpoints using shared resources, reducing overall system cost compared to equipping each endpoint with full memory and processing capabilities.
3Quantity of substance
If conventional energy metering systems are used, then overall consumption is monitored, but scalability is limited
Solution Approach 1:
The system architecture is segmented so that adding new endpoints only requires deploying additional simple data collection units that automatically connect to the existing centralized server. The server handles multiple clients simultaneously, enabling scalable growth without increasing per-device complexity.
Solution Approach 2:
The centralized server is designed as a universal platform that can serve multiple different endpoint devices simultaneously. It handles data collection, processing, storage, and reporting for numerous endpoints through a single infrastructure, enabling the system to scale by simply adding more endpoints to the existing server.
Data Source
AI summary
The present invention provides a method for monitoring and controlling power consumption at plurality endpoints. The method comprises, receiving raw data from plurality of endpoints, processing the raw data received from the plurality of the endpoints, communicating the processed data to a database using one or more protocols, interpreting the processed data into one or more events, measuring the power consumed by the plurality of the endpoints using the interpreted data; and controlling the power consumption of the plurality of the endpoints using one or more applications.