BuildingDepot 2.0: An Integrated Management System for Building Analysis and Control
Thomas Weng
Anthony Nwokafor
BuildSys '13 Proceedings of the Fourth ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings


Improving energy efficiency in buildings is a key objective for sensor researchers and promises significant reductions in energy usage across the world. The key technological driver for these gains are the novel sensor network deployments and the large amounts of data that they generate. The challenge however is making sense of this data, and using it effectively to design smarter building control schemes. Several recent research efforts have sought to address the challenge of data access and building control. However, while these systems have made progress in specific areas, many unanswered questions still revolve around data management and what exactly it means to develop building applications. Critically, how would such a solution work in a real building setting and how can applications be written such that they can be re-used in other settings? To resolve these issues we have developed BuildingDepot 2.0, a building management control platform that significantly updates on our first iteration of the system for data analysis and high level supervisory control.


author = {Weng, Thomas and Nwokafor, Anthony and Agarwal, Yuvraj},
year = {2013},
month = {11},
pages = {1-8},
title = {BuildingDepot 2.0: An Integrated Management System for Building Analysis and Control},
doi = {10.1145/2528282.2528285}

Plain Text

Weng, Thomas & Nwokafor, Anthony & Agarwal, Yuvraj. (2013). BuildingDepot 2.0: An Integrated Management System for Building Analysis and Control. 1-8. 10.1145/2528282.2528285.

Related Subprojects
BuildingDepot is essentially an Extensible and Distributed Architecture for Sensor Data Storage, Access and Sharing.It is a data storage, management, and actuation system for building-related data. Future smart buildings will generate an enormous amount of data from SCADA systems as well as deployed wireless sensor networks. Managing this data is a challenge, and using it to drive energy efficiency is even more difficult.