IoT Based Home Power Monitoring and Control

  Efficient control of home appliances and home power management is a challenging task. Many households struggle in maintaining the power budget and controlling the home appliances. The objective of the project is to design an Internet of Things (IoT) based system

Project Title

IoT Based Home Power Monitoring and Control

Project Area of Specialization

Internet of Things

Project Summary

Efficient control of home appliances and home power management is a challenging task. Many households struggle in maintaining the power budget and controlling the home appliances. The objective of the project is to design an Internet of Things (IoT) based system that can smartly monitor and efficiently control the home appliances. Proposed project can help in making the life easier by controlling all the household items powered by electricity on a single touch using a smartphone. The proposed design prototype can perform four major tasks. It will control home appliances, perform fault diagnosis, artificial intelligence-based electricity bill forecasting and generation of warning messages and alerts. A Raspberry Pi based server will intelligently monitor power usage statistics on daily basis. It will predict monthly electricity bill using machine learning and inform the user in advance. These calculations will be shared with the user through a mobile application. The user will also be able to control appliances in different rooms through the mobile application. The mobile application will also receive warning messages or notifications about any fault occurred in the system. The server can also shut down the appliances in a particular room if any fault is detected and notify the user on the mobile application.

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Project Objectives

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The objective of the project is to design an Internet of Things (IoT) based system that can monitor and efficiently control the home appliances. Proposed project can provide following features:

• It can perform monthly power budget prediction using machine learning.

• It can perform real time power monitoring and share power statistics with user.

• It can share power parameters, electricity budget and warning notifications on the mobile application with the user.

• It can perform fault diagnosis and perform actions accordingly.

• It can control the home appliances remotely through mobile application.

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Project Implementation Method

                   

                                                                             Figure 1. Project Block Diagram     

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The complete project is divided into four sections which include different type of circuitry and a controller to perform tasks. All these four sections are connected to the server through WIFI, and information is shared wirelessly among devices. The server further communicates with the mobile application for information flow. The server and ESP32 controller are separately powered up by DC power.

Data acquisition devices

The Current transformers, Potential transformers and power metering modules are used in each room for current and voltage data acquisition. The power consumed by each room is also measured by power metering module. For data acquisition purpose, PZEM-004t-V3 metering device is used. It can measure current, voltage, active power, reactive power, apparent power and power factor of each unit.

Microcontroller 

After data acquisition the collected data is read by microcontroller through analog input ports of the controller. After performing some basic calculations on received values the current and voltage data is shared with the server through WIFI. The microcontroller can also receive commands from server and switch the appliances accordingly through relays. The ESP32 Wi-Fi module is used for data collection in each room. The ESP32 controller wirelessly transmits this data to the server.

Server

The Raspberry-Pi based server is used in the project for control of home appliances, monitoring and AI based budget predictions. The server gets data from microcontroller installed in each room and a porch. The server performs different algorithms and machine learning techniques to predict the monthly power bill. The server can also perform fault diagnosis of home power system by analyzing the received data from microcontrollers. It can also generate warning messages for android based mobile application and share real time power statics with the mobile application. The server can also receive appliance switching commands from application directed by the users.

Wireless Connection

The server and controller of each room is connected wirelessly through WIFI connection. A messaging or data sharing protocol used for communication. A microcontroller wirelessly transmits the data to the server and it either takes some action or sends some more information back to the microcontroller wirelessly. All the appliances are wirelessly controlled using a mobile application even from far distances. The MQTT wireless communication protocol is used for communication between server and ESP32 controllers.

Relays for switching

Relays are used in each room for switching of appliances. The relays get control signal from microcontroller and from server. The low and heavy current appliances are switched by 10A relays and 20A relays, respectively. The relays are being use to switch on and off the connected loads of home like bulbs, fans and other home appliances.

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Benefits of the Project

The proposed project has many uses and benefits;

1. It can perform monthly power budget prediction.
2. It can provide facility of predefining the power budget.
3. It can perform real time power monitoring  and display power parameters on the mobile application in the form of graphs and tables.
4. It can perform fault diagnosis.
5. It can control the home appliances remotely through mobile application.

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Technical Details of Final Deliverable

The technical details of final deliverable of the project are given as follow:

• Proposed project will control and monitor 4 units (rooms) through an IoT platform with a Raspberry Pi based server

• For data acquisition in different rooms Esp32 based controllers are used

• Machine Learning based prediction is used for estimation of electricity bill and budget management

• An Android based mobile application is used to remotely control devices in various rooms and get user power statistics

• Proposed design will also perform fault diagnosis in different rooms and switch off respective devices accordingly

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Final Deliverable of the Project

HW/SW integrated system

Core Industry

Others

Other Industries

Core Technology

Internet of Things (IoT)

Other Technologies

Others

Sustainable Development Goals

Industry, Innovation and Infrastructure

Required Resources

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