Significant efforts are being made in the improvement of building automation and control systems in order to optimize the performance of buildings (e.g. reduction of energy consumption). As sensor networks in buildings increase, the complexity of managing them also increases. For instance, the generation and maintenance of metadata about sensors, such as their location within a building, currently requires significant manual labor. The research described in this paper explores the relationship between different HVAC system sensor measurements and physical characteristics of spaces, and its potential application in streamlining the identification of sensor location within a facility. The energy contained in the conditioned air delivered to each room is presented as a characteristic feature in order to understand the differences between rooms. Being able to understand the relationships between different measurement types and building characteristics is fundamental in achieving an automatic mapping of sensors in buildings, and this paper describes initial observations and results towards this goal.
This paper describes the experiences and lessons learned by a team of Civil and Environmental Engineering graduate students during a capstone project-based course, which orients students to acquire knowledge on sensing technologies, data management, systems engineering, and visualization concepts in order to design and implement an energy monitoring system in a three room lab space. The team, mentored by faculty members, was responsible for the deployment of hardware, establishing communications, database design and implementation, and developing visualizations to communicate the relevant information based on the requirements of a client role-played by a faculty member. Lessons learned from this project include the importance of applying a systems engineering approach during the iterative scope definition and design processes, and the use of alternative communications, learning, and problem-solving methods in order to tackle challenges of larger scope and complexity than presented in classroom-setting coursework, while working on a team environment.
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