V
Vishal Garg
Researcher at International Institute of Information Technology, Hyderabad
Publications - 70
Citations - 1290
Vishal Garg is an academic researcher from International Institute of Information Technology, Hyderabad. The author has contributed to research in topics: Energy consumption & Engineering. The author has an hindex of 15, co-authored 59 publications receiving 860 citations. Previous affiliations of Vishal Garg include International Institute of Minnesota & International Institute of Information Technology.
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Journal ArticleDOI
Smart occupancy sensors to reduce energy consumption
Vishal Garg,N.K. Bansal +1 more
TL;DR: Design of smart occupancy sensors which can adapt to changing activity levels are presented and about 5% more energy can be saved by using smart occupancy sensor as compared to non-adapting fixed TD sensors.
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Quantifying the direct benefits of cool roofs in an urban setting: Reduced cooling energy use and lowered greenhouse gas emissions
TL;DR: In this article, a field-based analytical method was developed to quantify cooling energy savings resulting from the installation of cool roofs on commercial buildings in the metropolitan Hyderabad region of India, where the measured annual energy savings from roof-whitening of previously black roofs ranged from 20 to 22kWh/m2 of roof area, corresponding to cooling energy use reduction of 14-26%.
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Robust short-term electrical load forecasting framework for commercial buildings using deep recurrent neural networks
Gopal Chitalia,Gopal Chitalia,Manisa Pipattanasomporn,Manisa Pipattanasomporn,Vishal Garg,Saifur Rahman +5 more
TL;DR: The forecasting results across all five buildings validate the robustness of the proposed deep learning framework for the short-term building-level electrical load forecasting tasks, and the formulated methods are found to be robust against weather forecasting errors.
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A review of open loop control strategies for shades, blinds and integrated lighting by use of real-time daylight prediction methods
Sneha Jain,Vishal Garg +1 more
TL;DR: Modified and improved open loop system are more competent as an alternative compared to the conventional methods for automated blind and lighting control systems and predict daylight more extensively, according to analysis of various daylight prediction methods.
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Evaluation of “Autotune” calibration against manual calibration of building energy models
TL;DR: In this article, the authors demonstrate the application of Autotune, a methodology aimed at automatically producing calibrated building energy models using measured data, in two case studies, by deliberately injecting faults into more than 60 parameters.