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Updated: Jan 29, 2026

A User-friendly and Powerful R Analysis of Large-scale Datasets
Published on: November 4, 2025
I-BLEND, a campus-scale commercial and residential buildings electrical energy dataset
Haroon Rashid1, Pushpendra Singh1, Amarjeet Singh1
1Computer Science and Engineering, OKhla Phase III, IIIT Delhi, New Delhi, 110020 India.
Abstract:
Efficient energy consumption at the building level is vital for sustainability. Providing energy efficient systems and solutions requires an understanding of how energy gets consumed. However, there is a general lack of large-scale open datasets about the energy consumption of buildings, which hinders the research. The recent emergence of smart energy meters makes it possible to collect such data, which can then be used for analysis. In this paper, we release I-BLEND, 52 months of electrical energy dataset at a one-minute sampling rate from commercial and residential buildings of an academic institute campus in an emerging economy, India. Also, we provide occupancy datasets at a 10-minute sampling rate for each of the campus buildings. To the best of our knowledge, this is the first such dataset from India. Public availability of such fine-granular data will allow users to perform different research tasks such as analyzing the impact of weather or occupancy schedule on energy consumption, detecting anomalies, and developing algorithms for predictive maintenance.
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