Wenchao Jiang, Zhimeng Yin, Ruofeng Liu, Zhijun Li, S. Kim, T. He
Cross-Technology Communication is a promising solution proposed recently to the coexistence problem of heterogeneous wireless technologies in the ISM bands. The existing works use only the coarse-grained packet-level information for cross-technology modulation, suffering from a low throughput (e.g., 10bps). Our approach, called BlueBee, proposes a new direction by emulating legitimate ZigBee frames using a Bluetooth radio. Uniquely, BlueBee achieves dual-standard compliance and transparency by selecting only the payload of Bluetooth frames, requiring neither hardware nor firmware changes at the Bluetooth senders and ZigBee receivers. Our implementation on both USRP and commodity devices shows that BlueBee can achieve a more than 99% accuracy and a throughput 10,000x faster than the state-of-the-art CTC reported so far.
{"title":"BlueBee: a 10,000x Faster Cross-Technology Communication via PHY Emulation","authors":"Wenchao Jiang, Zhimeng Yin, Ruofeng Liu, Zhijun Li, S. Kim, T. He","doi":"10.1145/3131672.3131678","DOIUrl":"https://doi.org/10.1145/3131672.3131678","url":null,"abstract":"Cross-Technology Communication is a promising solution proposed recently to the coexistence problem of heterogeneous wireless technologies in the ISM bands. The existing works use only the coarse-grained packet-level information for cross-technology modulation, suffering from a low throughput (e.g., 10bps). Our approach, called BlueBee, proposes a new direction by emulating legitimate ZigBee frames using a Bluetooth radio. Uniquely, BlueBee achieves dual-standard compliance and transparency by selecting only the payload of Bluetooth frames, requiring neither hardware nor firmware changes at the Bluetooth senders and ZigBee receivers. Our implementation on both USRP and commodity devices shows that BlueBee can achieve a more than 99% accuracy and a throughput 10,000x faster than the state-of-the-art CTC reported so far.","PeriodicalId":424262,"journal":{"name":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","volume":"238 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132420479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gabriele Miorandi, D. Quaglia, F. Fraccaroli, W. Vendraminetto, Enrico Giordano, M. Magno
Augmented reality (AR) applications greatly benefit from direction estimation. In current AR devices, direction estimation is enabled by power hungry technologies such as GPS, management of inertial data and video processing. We present a low-complexity eyewear prototype capable of obtaining directional information from a set of environmental radio sources by using a multi-antenna system patented by Wagoo LLC. Eyewear devices are the natural match for this technology under the assumption that user line of sight represents the main reference for user interaction and orientation. In the demonstration, the prototype detects when a user aims at objects or people that are associated to standard Bluetooth Low Energy emitters (beacons) with a current 30° sensitivity and 5% error rate.
{"title":"A Low-Complexity Eyewear System for Direction-based Augmented Reality Applications","authors":"Gabriele Miorandi, D. Quaglia, F. Fraccaroli, W. Vendraminetto, Enrico Giordano, M. Magno","doi":"10.1145/3131672.3136979","DOIUrl":"https://doi.org/10.1145/3131672.3136979","url":null,"abstract":"Augmented reality (AR) applications greatly benefit from direction estimation. In current AR devices, direction estimation is enabled by power hungry technologies such as GPS, management of inertial data and video processing. We present a low-complexity eyewear prototype capable of obtaining directional information from a set of environmental radio sources by using a multi-antenna system patented by Wagoo LLC. Eyewear devices are the natural match for this technology under the assumption that user line of sight represents the main reference for user interaction and orientation. In the demonstration, the prototype detects when a user aims at objects or people that are associated to standard Bluetooth Low Energy emitters (beacons) with a current 30° sensitivity and 5% error rate.","PeriodicalId":424262,"journal":{"name":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126794062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Individual localization services seldom satisfy the requirements for accurate, robust, punctual, and seamless location information. To enhance the provisioning, a set of challenges has to be addressed, pertaining to handover, fusion, and integration of individual localization services. In the following, we advertise the Standardized Localization Service (SLSR), a middleware architecture for achieving those goals. We instantiate the SLSR in a office-like indoor environment and evaluate its performance in a specifically designed testbed for evaluation of indoor localization approaches. Our results typify the contributions of different functional components envisioned in the SLSR on its overall performance.
{"title":"Standardized Localization Service","authors":"Filip Lemic, V. Handziski, A. Zubow, A. Wolisz","doi":"10.1145/3131672.3136959","DOIUrl":"https://doi.org/10.1145/3131672.3136959","url":null,"abstract":"Individual localization services seldom satisfy the requirements for accurate, robust, punctual, and seamless location information. To enhance the provisioning, a set of challenges has to be addressed, pertaining to handover, fusion, and integration of individual localization services. In the following, we advertise the Standardized Localization Service (SLSR), a middleware architecture for achieving those goals. We instantiate the SLSR in a office-like indoor environment and evaluate its performance in a specifically designed testbed for evaluation of indoor localization approaches. Our results typify the contributions of different functional components envisioned in the SLSR on its overall performance.","PeriodicalId":424262,"journal":{"name":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","volume":"1562 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128071933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this poster we present a graph-based hierarchical subchannel allocation scheme for V2V sidelink communications in Mode-3. Under this scheme, the eNodeB allocates subchannels for in-coverage vehicles. Then, vehicles will broadcast directly without the eNodeB intervening in the process. Therefore, in each communications cluster, it will become crucial to prevent allocation conflicts in time domain since vehicles will not be able to transmit and receive simultaneously. We present a solution where the time-domain requirement can be enforced through vertex aggregation. Additionally, allocation of subchannels is performed sequentially from the most to the least allocation-constrained cluster. We show through simulations that the proposed approach attains near-optimality.
{"title":"Hierarchical Subchannel Allocation for Mode-3 Vehicle-to-Vehicle Sidelink Communications","authors":"L. F. Abanto-Leon, A. Koppelaar, S. Groot","doi":"10.1145/3131672.3136987","DOIUrl":"https://doi.org/10.1145/3131672.3136987","url":null,"abstract":"In this poster we present a graph-based hierarchical subchannel allocation scheme for V2V sidelink communications in Mode-3. Under this scheme, the eNodeB allocates subchannels for in-coverage vehicles. Then, vehicles will broadcast directly without the eNodeB intervening in the process. Therefore, in each communications cluster, it will become crucial to prevent allocation conflicts in time domain since vehicles will not be able to transmit and receive simultaneously. We present a solution where the time-domain requirement can be enforced through vertex aggregation. Additionally, allocation of subchannels is performed sequentially from the most to the least allocation-constrained cluster. We show through simulations that the proposed approach attains near-optimality.","PeriodicalId":424262,"journal":{"name":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114509437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mathias Ciliberto, Francisco Javier Ordonez, H. Gjoreski, D. Roggen, S. Mekki, S. Valentin
We have completed the collection of one of the richest accurately annotated mobile dataset of modes of transportation and locomotion. To do this, we developed a highly reliable Android application called DataLogger capable of recording multisensor data from multiple synchronized smartphones simultaneously. The application allows real-time data annotation. We explain how we designed the app to achieve high reliability and ease of use. We also present an evaluation of the application in a big-data collection (750 hours, 950 GB of data, 17 different sensor modalities), analysing the data loss (less than 0.4%) and battery consumption (≈ 6% on average per hour). The application is available as open source.
{"title":"High reliability Android application for multidevice multimodal mobile data acquisition and annotation","authors":"Mathias Ciliberto, Francisco Javier Ordonez, H. Gjoreski, D. Roggen, S. Mekki, S. Valentin","doi":"10.1145/3131672.3136977","DOIUrl":"https://doi.org/10.1145/3131672.3136977","url":null,"abstract":"We have completed the collection of one of the richest accurately annotated mobile dataset of modes of transportation and locomotion. To do this, we developed a highly reliable Android application called DataLogger capable of recording multisensor data from multiple synchronized smartphones simultaneously. The application allows real-time data annotation. We explain how we designed the app to achieve high reliability and ease of use. We also present an evaluation of the application in a big-data collection (750 hours, 950 GB of data, 17 different sensor modalities), analysing the data loss (less than 0.4%) and battery consumption (≈ 6% on average per hour). The application is available as open source.","PeriodicalId":424262,"journal":{"name":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115461842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Continuous tracking of the device location in 3D space is a popular form of user input, especially for virtual/augmented reality (VR/AR), video games and health rehabilitation. Conventional inertial based approaches are well known for inaccuracy caused by large error drifts. Computer vision approaches can produce accuracy tracking but have privacy concerns and are subject to lighting conditions and computation complexity. Recent work exploits accurate acoustic distance measurements for high precision tracking. However, they require additional hardware (e.g., multiple external speakers), which adds to the costs and installation efforts, thus limiting the convenience and usability. In this paper, we propose BatTracker, which incorporates inertial and acoustic data for robust, high precision and infrastructure-free tracking in indoor environments. BatTracker leverages echoes from nearby objects and uses distance measurements from them to correct error accumulation in inertial based device position prediction. It incorporates Doppler shifts and echo amplitudes to reliably identify the association between echoes and objects despite noisy signals from multi-path reflection and cluttered environment. A probabilistic algorithm creates, prunes and evolves multiple hypotheses based on measurement evidences to accommodate uncertainty in device position. Experiments in real environments show that BatTracker can track a mobile device's movements in 3D space at sub-cm level accuracy, comparable to the state-of-the-art infrastructure based approaches, while eliminating the needs of any additional hardware.
{"title":"BatTracker: High Precision Infrastructure-free Mobile Device Tracking in Indoor Environments","authors":"Bing Zhou, Mohammed Elbadry, Ruipeng Gao, Fan Ye","doi":"10.1145/3131672.3131689","DOIUrl":"https://doi.org/10.1145/3131672.3131689","url":null,"abstract":"Continuous tracking of the device location in 3D space is a popular form of user input, especially for virtual/augmented reality (VR/AR), video games and health rehabilitation. Conventional inertial based approaches are well known for inaccuracy caused by large error drifts. Computer vision approaches can produce accuracy tracking but have privacy concerns and are subject to lighting conditions and computation complexity. Recent work exploits accurate acoustic distance measurements for high precision tracking. However, they require additional hardware (e.g., multiple external speakers), which adds to the costs and installation efforts, thus limiting the convenience and usability. In this paper, we propose BatTracker, which incorporates inertial and acoustic data for robust, high precision and infrastructure-free tracking in indoor environments. BatTracker leverages echoes from nearby objects and uses distance measurements from them to correct error accumulation in inertial based device position prediction. It incorporates Doppler shifts and echo amplitudes to reliably identify the association between echoes and objects despite noisy signals from multi-path reflection and cluttered environment. A probabilistic algorithm creates, prunes and evolves multiple hypotheses based on measurement evidences to accommodate uncertainty in device position. Experiments in real environments show that BatTracker can track a mobile device's movements in 3D space at sub-cm level accuracy, comparable to the state-of-the-art infrastructure based approaches, while eliminating the needs of any additional hardware.","PeriodicalId":424262,"journal":{"name":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122607049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ta-Cheng Chang, Liang Zheng, M. Gorlatova, C. Gitau, Ching-Yao Huang, M. Chiang
Fog computing, the distribution of computing resources closer to the end devices along the cloud-to-things continuum, is recently emerging as an architecture for scaling of the Internet of Things (IoT) sensor networking applications. Fog computing requires novel computing program decompositions for heterogeneous hierarchical settings. To evaluate these new decompositions, we designed, developed, and instrumented a fog computing testbed that includes cloud computing and computing gateway execution points collaborating to finish complex data analytics operations. In this interactive demonstration we present one fog-specific algorithmic decomposition we recently examined and adapted for fog computing: a multi-execution point linear regression decomposition that jointly optimizes operation latency, quality, and costs. The demonstration highlights the role fog computing can play in future sensor networking architectures, and highlights some of the challenges of creating computing program decompositions for these architectures. An annotated video of the demonstration is available at [5].
{"title":"Decomposing Data Analytics in Fog Networks","authors":"Ta-Cheng Chang, Liang Zheng, M. Gorlatova, C. Gitau, Ching-Yao Huang, M. Chiang","doi":"10.1145/3131672.3136962","DOIUrl":"https://doi.org/10.1145/3131672.3136962","url":null,"abstract":"Fog computing, the distribution of computing resources closer to the end devices along the cloud-to-things continuum, is recently emerging as an architecture for scaling of the Internet of Things (IoT) sensor networking applications. Fog computing requires novel computing program decompositions for heterogeneous hierarchical settings. To evaluate these new decompositions, we designed, developed, and instrumented a fog computing testbed that includes cloud computing and computing gateway execution points collaborating to finish complex data analytics operations. In this interactive demonstration we present one fog-specific algorithmic decomposition we recently examined and adapted for fog computing: a multi-execution point linear regression decomposition that jointly optimizes operation latency, quality, and costs. The demonstration highlights the role fog computing can play in future sensor networking architectures, and highlights some of the challenges of creating computing program decompositions for these architectures. An annotated video of the demonstration is available at [5].","PeriodicalId":424262,"journal":{"name":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130102029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ambuj Varshney, Laura Harms, C. Pérez-Penichet, C. Rohner, Frederik Hermans, T. Voigt
There is the long-standing assumption that radio communication in the range of hundreds of meters needs to consume mWs of power at the transmitting device. In this paper, we demonstrate that this is not necessarily the case for some devices equipped with backscatter radios. We present LOREA an architecture consisting of a tag, a reader and multiple carrier generators that overcomes the power, cost and range limitations of existing systems such as Computational Radio Frequency Identification (CRFID). LOREA achieves this by: First, generating narrow-band backscatter transmissions that improve receiver sensitivity. Second, mitigating self-interference without the complex designs employed on RFID readers by keeping carrier signal and backscattered signal apart in frequency. Finally, decoupling carrier generation from the reader and using devices such as WiFi routers and sensor nodes as a source of the carrier signal. An off-the-shelf implementation of LOREA costs 70 USD, a drastic reduction in price considering commercial RFID readers cost 2000 USD. LOREA's range scales with the carrier strength, and proximity to the carrier source and achieves a maximum range of 3.4 km when the tag is located at 1 m distance from a 28 dBm carrier source while consuming 70 μW at the tag. When the tag is equidistant from the carrier source and the receiver, we can communicate upto 75 m, a significant improvement over existing RFID readers.
{"title":"LoRea: A Backscatter Architecture that Achieves a Long Communication Range","authors":"Ambuj Varshney, Laura Harms, C. Pérez-Penichet, C. Rohner, Frederik Hermans, T. Voigt","doi":"10.1145/3131672.3131691","DOIUrl":"https://doi.org/10.1145/3131672.3131691","url":null,"abstract":"There is the long-standing assumption that radio communication in the range of hundreds of meters needs to consume mWs of power at the transmitting device. In this paper, we demonstrate that this is not necessarily the case for some devices equipped with backscatter radios. We present LOREA an architecture consisting of a tag, a reader and multiple carrier generators that overcomes the power, cost and range limitations of existing systems such as Computational Radio Frequency Identification (CRFID). LOREA achieves this by: First, generating narrow-band backscatter transmissions that improve receiver sensitivity. Second, mitigating self-interference without the complex designs employed on RFID readers by keeping carrier signal and backscattered signal apart in frequency. Finally, decoupling carrier generation from the reader and using devices such as WiFi routers and sensor nodes as a source of the carrier signal. An off-the-shelf implementation of LOREA costs 70 USD, a drastic reduction in price considering commercial RFID readers cost 2000 USD. LOREA's range scales with the carrier strength, and proximity to the carrier source and achieves a maximum range of 3.4 km when the tag is located at 1 m distance from a 28 dBm carrier source while consuming 70 μW at the tag. When the tag is equidistant from the carrier source and the receiver, we can communicate upto 75 m, a significant improvement over existing RFID readers.","PeriodicalId":424262,"journal":{"name":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130244113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
H. Gjoreski, Mathias Ciliberto, Francisco Javier Ordonez, D. Roggen, S. Mekki, S. Valentin
We explain how to obtain a highly versatile and precisely annotated dataset for the multimodal locomotion of mobile users. After presenting the experimental setup, data management challenges and potential applications, we conclude with the best practices for assuring data quality and reducing loss. The dataset currently comprises 7 months of measurements, collected by smartphone's sensors and a body-worn camera, while the 3 participants used 8 different modes of transportation. It comprises 950 GB of sensor data, which corresponds to 750 hours of labelled data. The obtained data will be useful for a wide range of research questions related to activity recognition, and will be made available to the community1.
{"title":"A Versatile Annotated Dataset for Multimodal Locomotion Analytics with Mobile Devices","authors":"H. Gjoreski, Mathias Ciliberto, Francisco Javier Ordonez, D. Roggen, S. Mekki, S. Valentin","doi":"10.1145/3131672.3136976","DOIUrl":"https://doi.org/10.1145/3131672.3136976","url":null,"abstract":"We explain how to obtain a highly versatile and precisely annotated dataset for the multimodal locomotion of mobile users. After presenting the experimental setup, data management challenges and potential applications, we conclude with the best practices for assuring data quality and reducing loss. The dataset currently comprises 7 months of measurements, collected by smartphone's sensors and a body-worn camera, while the 3 participants used 8 different modes of transportation. It comprises 950 GB of sensor data, which corresponds to 750 hours of labelled data. The obtained data will be useful for a wide range of research questions related to activity recognition, and will be made available to the community1.","PeriodicalId":424262,"journal":{"name":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127540568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We propose a novel method for mitigating erroneous wake-ups that are commonly associated with ultra-low power wake-up receivers. Recent research in low-power protocols has demonstrated significant improvements in energy-efficiency by employing ultra-low power wake-up receivers. However, due to the low-complexity receiver structures adopted, wake-up receivers are susceptible to external interference, which can cause the detection of non-existent wake-ups. The occurrence of these erroneous wake-ups wastes precious energy resources, thereby negating the potential energy savings in employing wake-up receivers. We address this challenging problem by extracting time-domain features from the output of the wake-up receiver, and construct a classifier to distinguish between correct and erroneous wake-ups. We describe the design of the proposed wake-up classifier and present preliminary results.
{"title":"Mitigating Erroneous Wake-ups","authors":"Felix Sutton, J. Beutel, L. Thiele","doi":"10.1145/3131672.3136980","DOIUrl":"https://doi.org/10.1145/3131672.3136980","url":null,"abstract":"We propose a novel method for mitigating erroneous wake-ups that are commonly associated with ultra-low power wake-up receivers. Recent research in low-power protocols has demonstrated significant improvements in energy-efficiency by employing ultra-low power wake-up receivers. However, due to the low-complexity receiver structures adopted, wake-up receivers are susceptible to external interference, which can cause the detection of non-existent wake-ups. The occurrence of these erroneous wake-ups wastes precious energy resources, thereby negating the potential energy savings in employing wake-up receivers. We address this challenging problem by extracting time-domain features from the output of the wake-up receiver, and construct a classifier to distinguish between correct and erroneous wake-ups. We describe the design of the proposed wake-up classifier and present preliminary results.","PeriodicalId":424262,"journal":{"name":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128713684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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