This study forecasts electricity demand in a smart grid environment. We present a prediction
method that uses a combination of forecasting values based on time-series clustering. The …

Reinforced concrete (RC) flat slabs, a popular choice in construction due to their flexibility,
are susceptible to sudden and brittle punching shear failure. Existing design methods often …

This study investigates the intricate relationship between electricity consumption in smart
office environments, temporal elements such as time, and external factors such as weather …

In this paper, we propose and design AuGrid, an LSTM-based model for geographically
aware smart grid service providers, which predicts the hourly load requests from users. We …

Los edificios son uno de los principales actores contaminantes del medio ambiente, por lo
que es necesario fortalecer las estrategias para la reducción de su consumo energético …

Nowadays Digital Display Boards (DDB) are used to post information in a variety of
locations, including public spaces, hospitals, general stores, institutions, and colleges …

With the rapid development of artificial intelligence and computer technology, grid
corporations have also begun to move towards comprehensive intelligence and …

Monitoring systems for the elderly gather a variety of information, including blood pressure,
insulin level, oxygen saturation, and more. Machine learning is a multidisciplinary method …

Electrical load prediction aids electrical producing and allocation firms in planning capacity
and management to ensure that all customers get the energy they need on a consistent …

Energy communities are legal entities that produce, store, and sell renewable energy (RE)
while also exchanging it inside the community via the public grid. They provide economic …