AI-Driven Control and Processing System for Smart Homes with Solar Energy
Journal Title: International Journal of Innovations in Science and Technology - Year 2024, Vol 6, Issue 4
Abstract
In recent years, the utilization of solar energy has grabbed attention in the industrial and domestic zones. The existing systems to use the services of solar cells are conventional. These systems require parameters (irradiance and temperature) for desirable results that are unknown to the end user. These parameters change with regions and human to human. Therefore, an Artificially Intelligent, Control and Processing System is designed to get more accurate results with the unique feature of empowering the end user, which uses the parameters assembled on different regions. The proposed system has an improved PV model based on (ANN) that resembles experimental results with a few readily available, reprogrammable input parameters from the PV module datasheet. The developed system uses regional irradiation data which exhibits minimal fluctuations. In the model presented here; to avoid overburdening problems, loads were divided into manageable chunks MK. In this case load chunks (needed) were moved from solar to utility more stably and economically. Briefly stated the suggested solution provides a complete package for integrating solar energy systems with the grid in an automated and resilient way.
Authors and Affiliations
AI-Driven Control and Processing System for Smart Homes with Solar Energy
Keywords
Related Articles
- EP ID EP760591
- DOI -
- Views 41
- Downloads 0
XDP-ML: A Game-Changer in Intrusion Detection Systems for Modern Cybersecurity
Intrusion Detection system (IDS) plays a vital role in cyber security. Traditional approaches are not good enough to detect properly the large threats. Machine learning provides a promising solution and good accuracy by...
Exploring the Influence of Teachers' Stress and Emotions on Student Behavior in Secondary Schools
The focus of this study is on the intricate relationship between the stress of the teacher, the emotion of the teacher, and the behavior of the workers in secondary school classrooms, stressing the bidirectional relati...
Leveraging CIELAB Segmentation and CNN for Wheat Fungi Disease Classification
Wheat is the third most harvested and consumed grain globally, but a significant portion of its production is wasted due to diseases. Fungal infections caused by pathogenic fungi are particularly harmful, greatly reduc...
Detection ofApplication-Layer Dos Attacks inIoTDevices Using Feature Selection andMachine Learning Models
With technological advancements, innovations like the Internet of Things (IoT) have become widespread, connecting more devices to the Internet. However, as the number of connected devices increases, cyber-attacks—espec...
Python Based Estimation ofGroundwater Quality Along Hudaira Drain
During periods of restricted access to fresh surface water, enterprises depend on underground water reserves to meet their growing demands. Groundwater is crucial for fulfilling the growing demands of families, agricul...