TY - GEN
T1 - SeleCon
T2 - 2nd IEEE/ACM International Conference on Internet-of-Things Design and Implementation, IoTDI 2017
AU - Alanwar, Amr
AU - Alzantot, Moustafa
AU - Ho, Bo Jhang
AU - Martin, Paul
AU - Srivastava, Mani
N1 - Publisher Copyright:
© 2017 ACM.
PY - 2017/4/18
Y1 - 2017/4/18
N2 - Although different interaction modalities have been proposed in the field of human-computer interface (HCI), only a few of these techniques could reach the end users because of scalability and usability issues. Given the popularity and the growing number of IoT devices, selecting one out of many devices becomes a hurdle in a typical smarthome environment. Therefore, an easy-to-learn, scalable, and non-intrusive interaction modality has to be explored. In this paper, we propose a pointing approach to interact with devices, as pointing is arguably a natural way for device selection. We introduce SeleCon for device selection and control which uses an ultra-wideband (UWB) equipped smartwatch. To interact with a device in our system, people can point to the device to select it then draw a hand gesture in the air to specify a control action. To this end, SeleCon employs inertial sensors for pointing gesture detection and a UWB transceiver for identifying the selected device from ranging measurements. Furthermore, SeleCon supports an alphabet of gestures that can be used for controlling the selected devices. We performed our experiment in a 9m-by-10m lab space with eight deployed devices. The results demonstrate that SeleCon can achieve 84:5% accuracy for device selection and 97% accuracy for hand gesture recognition. We also show that SeleCon is power efficient to sustain daily use by turning o? the UWB transceiver, when a user's wrist is stationary.
AB - Although different interaction modalities have been proposed in the field of human-computer interface (HCI), only a few of these techniques could reach the end users because of scalability and usability issues. Given the popularity and the growing number of IoT devices, selecting one out of many devices becomes a hurdle in a typical smarthome environment. Therefore, an easy-to-learn, scalable, and non-intrusive interaction modality has to be explored. In this paper, we propose a pointing approach to interact with devices, as pointing is arguably a natural way for device selection. We introduce SeleCon for device selection and control which uses an ultra-wideband (UWB) equipped smartwatch. To interact with a device in our system, people can point to the device to select it then draw a hand gesture in the air to specify a control action. To this end, SeleCon employs inertial sensors for pointing gesture detection and a UWB transceiver for identifying the selected device from ranging measurements. Furthermore, SeleCon supports an alphabet of gestures that can be used for controlling the selected devices. We performed our experiment in a 9m-by-10m lab space with eight deployed devices. The results demonstrate that SeleCon can achieve 84:5% accuracy for device selection and 97% accuracy for hand gesture recognition. We also show that SeleCon is power efficient to sustain daily use by turning o? the UWB transceiver, when a user's wrist is stationary.
KW - Hand gestures
KW - IoT
KW - Pointing
UR - http://www.scopus.com/inward/record.url?scp=85019043319&partnerID=8YFLogxK
U2 - 10.1145/3054977.3054981
DO - 10.1145/3054977.3054981
M3 - Conference contribution
AN - SCOPUS:85019043319
T3 - Proceedings - 2017 IEEE/ACM 2nd International Conference on Internet-of-Things Design and Implementation, IoTDI 2017 (part of CPS Week)
SP - 47
EP - 58
BT - Proceedings - 2017 IEEE/ACM 2nd International Conference on Internet-of-Things Design and Implementation, IoTDI 2017 (part of CPS Week)
PB - Association for Computing Machinery, Inc
Y2 - 18 April 2017 through 20 April 2017
ER -