IOE based building energy profiling system

We will acquire data from the sensors which includes voltage sensors,current sensors etc. With the help of the data acquired prediction will be made and controlling will be executed of the appliances.Prediction will be done using the machine learning algorithms.Controlling would be executed through

Project Title

IOE based building energy profiling system

Project Area of Specialization

Electrical/Electronic Engineering

Project Summary

We will acquire data from the sensors which includes voltage sensors,current sensors etc. With the help of the data acquired prediction will be made and controlling will be executed of the appliances.Prediction will be done using the machine learning algorithms.Controlling would be executed through the android app and web app, which will monitor all the incoming real-time data and a plus point of this real-time data is it will indicate us that whether the appliances are working or not, or whether they are operational or not. Utmost benefit that we are offering is the safety prospect in this project. With the help of fire detection safety measures are executed.Provided any situation the alarm would indicate us the situations which includes power use whether the power is fluctuating or not so basically it will indicate us about the fluctuations. Sehcduling of appliances to turn on and off the appliances. 

Project Objectives

Below are the objectives that we have worked for.

Ø Buildings are identified as the major energy consumers worldwide

Ø Making them energy efficient is extremely crucial

Ø Building energy Is the need to guarantee the sustainable development of national economy

Ø Using the concept of IoE collecting data from sensors to compute energy and profile that energy for further use.

Project Implementation Method

We have done the interfacing of the current,voltage and smoke sensors with the arduino which has been used in our project as a microcontroller. A wifi module has been used with microcontroller which would provide the wifi access to the microcontroller to send the incoming real-time data on the internet.

We have used Node-red as a platform to control the appliances with the help of an android application. This has been done using MQTT protocols in the Node-red.

Another method has been used to publish the data directly on the html fire based cloud.In this method also we have done the controlling of the appliances.This method provides us the access on the internet where we can publish our incoming real-time data directly on the internet.

After publishing the data on the html website we can even control the data from the html interface.

After acquiriing the data from the sensors we have implemented the machine learning algorithms on the incoming real-time data for prediction of future electricity consumption, billing is also done which can give an idea about the units being consumed and ultimately forming a bill.

Benefits of the Project

Following are the benefits of our project discussed below.

• Advance billing prediction is a benefit that we are providing. With the help of this anyone would be able to have a rough idea about his/her monthly units consumption.

• Energy management can also be done. This features provides you the benefit of controlling your energy consumption. With the help of controlling energy one can manage his/her bills. Energy can be controlled by turning on/off some of the appliances that are consuming extra energy at that particular moment.

• Our project also helps in controlling the appliances by sitting anywhere in the world. It does not matter where one would go, if he/she forgot to turn off some unneeded appliances he/she can directly control the appliances through the html intterface and android app.

• Utmost benefit that we are offering is the safety prospect in this project. With the help of fire detection safety measures are executed.Provided any situation the alarm would indicate us the situations which includes power use whether the power is fluctuating or not so basically it will indicate us about the fluctuations.

Technical Details of Final Deliverable

• We will acquire data from the sensors which includes voltage sensors,current sensors etc. With the help of the data acquired prediction will be made and controlling will be executed of the appliances.
• Prediction will be done using the machine learning algorithms.
• Controlling would be executed through the android app and web app, which will monitor all the incoming real-time data and a plus point of this real-time data is it will indicate us that whether the appliances are working or not, or whether they are operational or not.
• We are offering  the safety prospect in this project. With the help of fire detection safety measures are executed.Provided any situation the alarm would indicate us the situations which includes power use whether the power is fluctuating or not so basically it will indicate us about the fluctuations.
• Sehcduling of appliances to turn on and off the appliances. 
• Real-time monitoring and controlling is being done using fire based data base which is connected to an android app and html interface.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Energy

Other Industries

Others , Telecommunication

Core Technology

Cloud Infrastructure

Other Technologies

Internet of Things (IoT), Others

Sustainable Development Goals

Affordable and Clean Energy, Decent Work and Economic Growth

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com