Power Consumption Analytics

Power Consumption Analytics is a real-time IoT-based energy management system designed to monitor and optimize energy usage. By combining smart meters, cloud computing with ThingSpeak, and a mobile app developed with Flutter, this system offers an intuitive solution for efficient energy management, providing users with insights into their power consumption, detecting anomalies, and optimizing energy usage.

Key Features

• Real-time Power Monitoring: Track voltage, power factor, and consumption trends.
• Anomaly Detection: Instant alerts for overvoltage or low power factor deviations.
• Cloud Integration: Data storage and processing on ThingSpeak cloud platform.
• User Interface: A dynamic Flutter-based mobile app that visualizes data and provides real-time analytics.
• Scalability: Supports growing numbers of devices and users, ideal for both small and large-scale applications.

System Overview

The architecture consists of three key layers:

1. Input Layer: IoT smart meters measuring key electrical parameters.
2. Processing Layer: ThingSpeak for cloud-based data processing and analytics.
3. Output Layer: A user-friendly mobile interface built with Flutter to display real-time data, alerts, and consumption reports.

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Getting Started

To set up and run the system, follow these steps:

Prerequisites

• ThingSpeak Account: Sign up for an account on ThingSpeak.
• Flutter SDK: Install Flutter from Flutter's official site.
• Smart Meters: IoT devices with Wi-Fi or Zigbee support to transmit data.

Installation Steps:

1. Clone the repository:

   git clone https://github.com/rprakashdass/power_consumption_analytics.git
   cd power_consumption_analytics

2. Set up ThingSpeak:

   • Create a new channel on ThingSpeak and generate API keys.

3. Configure IoT devices to transmit data to ThingSpeak via REST APIs.

4. Build and run the Flutter app:

   flutter run

5. Monitor and optimize energy usage using the real-time dashboards and alerts in the app.

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Team Members

• Muthuraja M - GitHub
• Krishnan T - GitHub
• Prakash Dass R - GitHub
• Deepak Kumaran RMG - GitHub
• Bharath G - GitHub

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License

This project is licensed under the MIT License - see the LICENSE file for details.