| 1. |
- Narayana, S., et al.
(författare)
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LOCI : privacy-aware, device-free, low-power localization of multiple persons using IR sensors
- 2020
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Ingår i: Proceedings - 2020 19th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2020. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728154978 - 9781728154985 ; , s. 121-132
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Konferensbidrag (refereegranskat)abstract
- High accuracy and device-free indoor localization is still a holy grail to enable smart environments. With the growing privacy concerns and regulations, it is necessary to develop methods and systems that can be low-power, device-free as well as privacy-aware. While IR-based solutions fit the bill, they require many modules to be installed in the area of interest for higher accuracy, or proper planning during installation, or they may not work if the background has multiple heat-emitting objects, etc. In this paper, we propose a custom-built miniature device called LOCI that uses IR sensing. One unit of LOCI can provide three-dimensional localization at best. LOCI uses only a thermopile and a PIR sensor built within a 5x5x2 cm3 module. Since IR-based sensing is used, LOCI consumes around 80 mW. LOCI uses analog waveform from the PIR sensor with the gain of the PIR sensor dynamically controlled through software in real-time to simulate spatial diversity. LOCI proposes low-complexity techniques with sensor fusion to eliminate the noise in the background, which has not been handled in previous works even with sophisticated signal processing techniques. Since LOCI uses raw data from the thermopile, the computations are power-efficient. We present the complete design of LOCI and the proposed methodology to estimate height and location. LOCI achieves accuracies of sub-22 cm with a confidence of 0.5 and sub-35 cm with a confidence of 0.8. The best-case location accuracy is 12.5 cm. The accuracy of height estimation is within 8 cm in majority cases. LOCI can easily be extended to recognize activities.
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| 2. |
- Pérez-Penichet, Carlos, et al.
(författare)
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TagAlong : efficient integration of battery-free sensor tags in standard wireless networks
- 2020
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Ingår i: Proceedings - 2020 19th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2020. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728154978 ; , s. 169-180
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Konferensbidrag (refereegranskat)abstract
- New battery-free sensor tags that interoperate with unmodified standard IoT devices can extend a sensor network's capabilities in a scalable and cost-effective manner. The tags achieve battery-free operation through backscatter-related techniques, while the standard IoT devices can provide the necessary unmodulated carrier, avoiding additional dedicated infrastructure. However, this approach presents multiple challenges: It requires coordination between nodes transmitting, receiving and generating carrier, adds extra latency and energy consumption to already constrained devices, and increases interference and contention in shared spectrum. We present TagAlong, a medium access mechanism for interoperable sensor tags that, besides coordinating, optimizes the use of carrier generators, minimizing the disruption caused to the operation of the regular nodes. We accomplish this by parallelizing communications with battery-free tags when possible, sharing carriers for multiple tags concurrently and synchronizing communications with tags that share carrier generators. We demonstrate the feasibility of TagAlong in a testbed deployment. In our evaluation we find that it can reduce the duration of the tags' schedule by 60% while improving the energy and spectrum usage by 30% when compared to sequential interrogation with no difference in reliability.
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