Idea - FICS

Sustainable Home

Team and Contact Details

Student Name School Degree Year Email
Talha KamranSEECSUndergraduateFourthtkamran.bee17seecs@seecs.edu.pk
Muhammad Afnan AftabSEECSUndergraduateFourthhaftab.bee17seecs@seecs.edu.pk
Muhammad Talha AmirSEECSUndergraduateFourthmamir.bee17seecs@seecs.edu.pk

Inter School Idea ? No
Do you need expertises from another area: No
If Yes please provide details of expertises you need:

Idea Details

Idea Name: Sustainable Home
Slogan: IoT based Home Solar System
Supervisor Name: Dr. Syed Muhammad Hassan Zaidi
Supervisor Designation: Senior Faculty Member
Supervisor School: School of Electrical Engineering and Computer Science (SEECS)
Supervisor Department: Electrical Engineering (EE)
Contact number: 03075558722
Email ID: drzaidi@seecs.edu.pk
Abstract:
    To reduce dependence on the grid, we propose an IoT system that can monitor power consumption and generation. We applied machine learning algorithms for solar forecasting and demand-side management.
What is the unmet need in society that your idea will fulfill ?
    To fulfill energy requirements, every house needs renewable energy sources to self-sustain. Our solution is a positive step toward sustainable and smart cities. IoT system makes routine tasks easy as well.
Who needs it ? How many would benefit ?
   As people are installing solar panels, everyone will want to reduce their electricity bills. Our system will be needed by people living in cities to effectively utilize solar power and by people in remote areas who face electricity shortages.
How will the solution works
    Solar power generation will be monitored by a watt-hour meter. A battery bank will store excess solar power. The loads will be controlled by IoT nodes that will monitor their power consumption. All this data will be sent wirelessly to the cloud-connected web portal where machine learning algorithms will be applied to predict future power generation and consumption and increase the efficiency of our system by effectively utilizing available solar power and shedding loads during less power.
Who are your competitors ? How is your solution different
    There are smart solution providers in the country but no one makes use of machine learning to predict future power generation and consumption. Our competitors allow users to control loads but we also provide a solution to effectively utilize available solar power and shed loads when needed.
Status: new
Entry Date & Time: 2021-01-06 (1053)