TY - GEN
T1 - Smart lighting control using oblivious mobile sensors
AU - Karapetyan, Areg
AU - Chau, Sid Chi Kin
AU - Elbassioni, Khaled
AU - Khonji, Majid
AU - Dababseh, Emad
N1 - Publisher Copyright:
© 2018 Association for Computing Machinery.
PY - 2018/11/7
Y1 - 2018/11/7
N2 - The interplay of smart light bulbs (equipped with wireless controllable LEDs) and mobile sensors (embedded in wearable devices, such as smart watches and spectacles) enables a wide range of interactive lighting applications. One notable example is a smart lighting control system that provides automated illuminance management by wearable sensors close to end-users. In this paper, an energyefficient smart lighting control system is developed using mobile light sensors for measuring local illuminance and assisting smart light bulbs to coordinate the brightness adjustments, while meeting users' heterogeneous lighting preferences. A pivotal challenge in these systems is attributed to the presence of oblivious mobile sensors hampered by the uncertainties in their relative locations to light bulbs, unknown indoor environment and time-varying background light sources. To cope with these hindrances, we devise an effective model-agnostic control algorithm inducing continuous adaptive coordination of oblivious mobile sensors without complete knowledge of dynamic operational environment and the associated parameters. The proposed algorithm is corroborated extensively under diverse settings and scenarios in a proof-of-concept smart lighting testbed featuring programmable light bulbs and smartphones, deployed as light sensing units. Lastly, we discuss some practical limitations of the proposed control approach, along with possible solutions, and conclude by outlining promising directions for future work.
AB - The interplay of smart light bulbs (equipped with wireless controllable LEDs) and mobile sensors (embedded in wearable devices, such as smart watches and spectacles) enables a wide range of interactive lighting applications. One notable example is a smart lighting control system that provides automated illuminance management by wearable sensors close to end-users. In this paper, an energyefficient smart lighting control system is developed using mobile light sensors for measuring local illuminance and assisting smart light bulbs to coordinate the brightness adjustments, while meeting users' heterogeneous lighting preferences. A pivotal challenge in these systems is attributed to the presence of oblivious mobile sensors hampered by the uncertainties in their relative locations to light bulbs, unknown indoor environment and time-varying background light sources. To cope with these hindrances, we devise an effective model-agnostic control algorithm inducing continuous adaptive coordination of oblivious mobile sensors without complete knowledge of dynamic operational environment and the associated parameters. The proposed algorithm is corroborated extensively under diverse settings and scenarios in a proof-of-concept smart lighting testbed featuring programmable light bulbs and smartphones, deployed as light sensing units. Lastly, we discuss some practical limitations of the proposed control approach, along with possible solutions, and conclude by outlining promising directions for future work.
KW - Illuminance Control Algorithm
KW - Internet-of-Things
KW - Oblivious Mobile Sensors
KW - Smart Lighting Control
KW - Wearable Computing
UR - http://www.scopus.com/inward/record.url?scp=85058421270&partnerID=8YFLogxK
U2 - 10.1145/3276774.3276788
DO - 10.1145/3276774.3276788
M3 - Conference contribution
T3 - BuildSys 2018 - Proceedings of the 5th Conference on Systems for Built Environments
SP - 158
EP - 167
BT - BuildSys 2018 - Proceedings of the 5th Conference on Systems for Built Environments
A2 - Ramachandran, Gowri Sankar
A2 - Batra, Nipun
PB - Association for Computing Machinery, Inc
T2 - 5th ACM International Conference on Systems for Built Environments, BuildSys 2018
Y2 - 7 November 2018 through 8 November 2018
ER -