Paper
15 April 2011 Data acquisition and interpretation in order to anticipate the behavior of a resident for biofication of living spaces
Kosuke Ohashi, Akira Mita
Author Affiliations +
Abstract
Current smart buildings are designed based on prescribed scenarios so that they cannot deal with unexpected events. Moreover, they do not evolve by themselves. "Biofication of Living Spaces" is a concept in which we aim to make living spaces safer and more comfortable by embedding autonomous mechanisms in them. The key technologies for biofication are sensor networks to acquire information and data-processing technologies for effective utilization of information. As a first step towards the realization of "Biofication of Living Spaces", a system for acquiring and storing information must be developed. This research will propose a system database to control a comfortable space. As a first step towards realizing "Biofication of Living Spaces", a system for acquiring and storing information must be developed. This system is similar to the functions of physiological adaption. This research suggests a data model and a database for biofication. This database system is built for living space control based on physiological action. It focuses on "hormone". Hormone is an important factor for transmitting information. While human is in a room, he/she emits unpleasant information to the environment. A sensor agent robot collects these data, and change to "unpleasant hormone". In this system, a sensor agent robot collects data. It can follow residents and acquire data at any point. From these hormones, this system controls all devices in the room. At last, evidence, scalability and robustness are tested.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kosuke Ohashi and Akira Mita "Data acquisition and interpretation in order to anticipate the behavior of a resident for biofication of living spaces", Proc. SPIE 7981, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2011, 79813Y (15 April 2011); https://doi.org/10.1117/12.880203
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Cited by 1 scholarly publication.
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KEYWORDS
Data modeling

Databases

Control systems

Sensors

Data acquisition

Environmental sensing

Buildings

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