Xiaolin Fang, Junzhou Luo, Hong Gao, Weiwei Wu, Siyao Cheng, Zhipeng Cai
{"title":"Detecting deterioration of nearsightness","authors":"Xiaolin Fang, Junzhou Luo, Hong Gao, Weiwei Wu, Siyao Cheng, Zhipeng Cai","doi":"10.1145/2737095.2742558","DOIUrl":"https://doi.org/10.1145/2737095.2742558","url":null,"abstract":"Myopia becomes a more and more serious worldwide problem as the number of myopic people (especially young people) grows rapidly. Efficient methods are required to monitoring the deterioration of nearsightness so as to take further treatment. This demo realizes a noval nearsightness monitoring system, called iSee, which utilizes the widely used smartphones to detect the deterioration of nearsightness by monitoring and analysing the the distance between the eyes and the smartphone screen. A prototype of iSee has been developed to evaluated the effectiveness under different environmental conditions.","PeriodicalId":318992,"journal":{"name":"Proceedings of the 14th International Conference on Information Processing in Sensor Networks","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127453981","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}
Anh Luong, Spencer Madsen, Michael Empey, Neal Patwari
{"title":"RUBreathing: non-contact real time respiratory rate monitoring system","authors":"Anh Luong, Spencer Madsen, Michael Empey, Neal Patwari","doi":"10.1145/2737095.2737133","DOIUrl":"https://doi.org/10.1145/2737095.2737133","url":null,"abstract":"The respiration rate of a person provides critical information about their well-being. Conventionally, contact sensing is used for breathing monitoring; however, it is expensive, uncomfortable, and immobile. In-home non-contact breathing monitoring is now possible via Doppler radar and motion capture video sensors, yet these technologies are limited in mobility, among other limitations. When monitoring a patient who is free to move around his or her home, it is dificult to scale current non-contact sensors to cover the large area. Our RUBreathing sensor system uses RF received signal strength (RSS) in a network to estimate breathing rate in real-time with high accuracy over a wide area. In this demonstration, we show the sensor continuously estimating a patient's respiration rate from non-contact RSS measurements between wireless devices.","PeriodicalId":318992,"journal":{"name":"Proceedings of the 14th International Conference on Information Processing in Sensor Networks","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127930784","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}
Y. R. Venugopalakrishna, C. Murthy, P. Misra, J. Warrior
{"title":"A column matching based algorithm for target self-localization using beacon nodes","authors":"Y. R. Venugopalakrishna, C. Murthy, P. Misra, J. Warrior","doi":"10.1145/2737095.2742935","DOIUrl":"https://doi.org/10.1145/2737095.2742935","url":null,"abstract":"In this work, an algorithm is proposed for self-localization of a target node using power measurements from beacon nodes transmitting from known locations. The geographical area is overlaid with a virtual grid, and the problem is treated as one of testing overlapping subsets of grid cells for the presence of the target node. The proposed algorithm is validated both by Monte Carlo simulations as well as using experimental data collected from commercially-off-the-shelf bluetooth low energy (BLE) beacon nodes.","PeriodicalId":318992,"journal":{"name":"Proceedings of the 14th International Conference on Information Processing in Sensor Networks","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129539726","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}
{"title":"Tongue-n-cheek: non-contact tongue gesture recognition","authors":"Zheng Li, R. Robucci, Nilanjan Banerjee, C. Patel","doi":"10.1145/2737095.2737109","DOIUrl":"https://doi.org/10.1145/2737095.2737109","url":null,"abstract":"Tongue gestures are a key modality for augmentative and alternative communication in patients suffering from speech impairments and full-body paralysis. Systems for recognizing tongue gestures, however, are highly intrusive. They either rely on magnetic sensors built into dentures or artificial teeth deployed inside a patient's mouth or require contact with the skin using electromyography (EMG) sensors. Deploying sensors inside a patient's mouth can be uncomfortable for long-term use and contact-based sensors like EMG electrodes can cause skin abrasion. To address this problem, we present a novel contact-less sensor, called Tongue-n-Cheek, that captures tongue gestures using an array of micro-radars. The array of micro-radars act as proximity sensors and capture muscle movements when the patient performs the tongue gesture. Tongue-n-Cheek converts these movements into gestures using a novel signal processing algorithm. We demonstrate the efficacy of Tongue-n-Cheek and show that our system can reliably infer gestures with 95% accuracy and low latency.","PeriodicalId":318992,"journal":{"name":"Proceedings of the 14th International Conference on Information Processing in Sensor Networks","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127657152","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}
Matthew Tan Creti, V. Sundaram, S. Bagchi, P. Eugster
{"title":"Software-only system-level record and replay in wireless sensor networks","authors":"Matthew Tan Creti, V. Sundaram, S. Bagchi, P. Eugster","doi":"10.1145/2737095.2741839","DOIUrl":"https://doi.org/10.1145/2737095.2741839","url":null,"abstract":"Wireless sensor networks (WSNs) are plagued by the possibility of bugs manifesting only at deployment. However, debugging deployed WSNs is challenging for several reasons---the remote location of deployed sensor nodes, the non- determinism of execution that can make it difficult to replicate a buggy run, and the limited hardware resources available on a node. In particular, existing solutions to record and replay debugging in WSNs fail to capture the complete code execution, thus negating the possibility of a faithful replay and causing a large class of bugs to go unnoticed. In short, record and replay logs a trace of predefined events while a deployed application is executing, enabling replaying of events later using debugging tools. Existing recording methods fail due to the many sources of non-determinism and the scarcity of resources on nodes. In this demo, we present Trace And Replay Debugging In Sensornets (Tardis), a software-only approach for deterministic record and replay of WSN nodes. Tardis is able to record all sources of non-determinism, based on the observation that such information is compressible using a combination of techniques specialized for respective sources. Despite their domain-specific nature, the techniques presented are applicable to the broader class of resource-constrained embedded systems.","PeriodicalId":318992,"journal":{"name":"Proceedings of the 14th International Conference on Information Processing in Sensor Networks","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121365400","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}
{"title":"Improving the error drift of inertial navigation based indoor location tracking","authors":"Sourjya Sarkar, Avik Ghose, Archan Misra","doi":"10.1145/2737095.2742936","DOIUrl":"https://doi.org/10.1145/2737095.2742936","url":null,"abstract":"Inertial sensing based indoor localization currently requires fairly precise layout maps, to help provide constraints and landmarks that bound the error drift. In this paper, we seek to improve the accuracy of one component of inertial-based tracking, namely the estimation of an individual's stride-length, so as to reduce the cumulative drift. We show that an individual's stride-length is affected by both his/her movement speed and heading-changes in the trajectory, and present an adaptive, online stride-length estimation algorithm that learns appropriate stride-length distributions for different (speed, heading) combinations. Initial experiments conducted using our proposed approach in combination with state-of-the-art step counting and heading estimation techniques, reduce the 95th percentile of average localization error by ≈ 30%. We thus envisage that inertial tracking may become practical even with coarse-grained map information.","PeriodicalId":318992,"journal":{"name":"Proceedings of the 14th International Conference on Information Processing in Sensor Networks","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124012865","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}
V. Rajaraman, P. Misra, Kumaresh Dhotrad, J. Warrior
{"title":"Enabling plug-n-play for the internet of things with self describing devices","authors":"V. Rajaraman, P. Misra, Kumaresh Dhotrad, J. Warrior","doi":"10.1145/2737095.2742927","DOIUrl":"https://doi.org/10.1145/2737095.2742927","url":null,"abstract":"The primal problem with the Internet of Things is the lack of interoperability at various levels, and more predominately at the device level. While there exists multitude of platforms from multiple manufacturers, the existing ecosystem still remains highly closed. In this work, we propose SNaaS or Sensor/Network as a Service: a service layer that enables the creation of the plug-n-play infrastructure, across platforms from multiple vendors, necessary for interoperability and successful deployment of large-scale systems. We present the design and implementation of SNaaS, along with preliminary microbenchmarks.","PeriodicalId":318992,"journal":{"name":"Proceedings of the 14th International Conference on Information Processing in Sensor Networks","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131008909","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}
Damian Pfammatter, D. Giustiniano, Vincent Lenders
{"title":"A software-defined sensor architecture for large-scale wideband spectrum monitoring","authors":"Damian Pfammatter, D. Giustiniano, Vincent Lenders","doi":"10.1145/2737095.2737119","DOIUrl":"https://doi.org/10.1145/2737095.2737119","url":null,"abstract":"Today's spectrum measurements are mainly performed by governmental agencies which drive around using expensive specialized hardware. The idea of crowdsourcing spectrum monitoring has recently gained attention as an alternative way to capture the usage of wide portions of the wireless spectrum at larger geographical and time scales. To support this vision, we develop a flexible software-defined sensor architecture that enables distributed data collection in real-time over the Internet. Our sensor design builds upon low-cost commercial off-the-shelf (COTS) hardware components with a total cost per sensor device below $100. The low-cost nature of our sensor platform makes the sensing approach particularly suitable for large-scale deployments but imposes technical challenges regarding performance and quality. To circumvent the limits of our solution, we have implemented and evaluated different sensing strategies and noise reduction techniques. Our results suggest that our sensor architecture may be useful in application areas such as dynamic spectrum access in cognitive radios, detecting regions with elevated electro-smog, or simply to gain an understanding of the spectrum usage for advanced signal intelligence such as anomaly detection or policy enforcement.","PeriodicalId":318992,"journal":{"name":"Proceedings of the 14th International Conference on Information Processing in Sensor Networks","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126942523","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}
S. Nasser, Andew Barry, Marek Doniec, Guy Peled, G. Rosman, D. Rus, M. Volkov, Dan Feldman
{"title":"Fleye on the car: big data meets the internet of things","authors":"S. Nasser, Andew Barry, Marek Doniec, Guy Peled, G. Rosman, D. Rus, M. Volkov, Dan Feldman","doi":"10.1145/2737095.2742919","DOIUrl":"https://doi.org/10.1145/2737095.2742919","url":null,"abstract":"Vehicle-based vision algorithms, such as the collision alert systems [4], are able to interpret a scene in real-time and provide drivers with immediate feedback. However, such technologies are based on cameras on the car, limited to the vicinity of the car, severely limiting their potential. They cannot find empty parking slots, bypass traffic jams, or warn about dangers outside the car's immediate surrounding. An intelligent driving system augmented with additional sensors and network inputs may significantly reduce the number of accidents, improve traffic congestion, and care for the safety and quality of people's lives. We propose an open-code system, called Fleye, that consists of an autonomous drone (nano quadrotor) that carries a radio camera and flies few meters in front and above the car. The streaming video is transmitted in real time from the quadcopter to Amazon's EC2 cloud together with information about the driver, the drone, and the car's state. The output is then transmitted to the \"smart glasses\" of the driver. The control of the drone, as well as the sensor data collection from the driver, is done by low cost (<30$) minicomputer. Most computation is done in the cloud, allowing straightforward integration of multiple vehicle behaviour and additional sensors, as well as greater computational capability.","PeriodicalId":318992,"journal":{"name":"Proceedings of the 14th International Conference on Information Processing in Sensor Networks","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126688194","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}
Roberto Calvo-Palomino, Damian Pfammatter, D. Giustiniano, Vincent Lenders
{"title":"A low-cost sensor platform for large-scale wideband spectrum monitoring","authors":"Roberto Calvo-Palomino, Damian Pfammatter, D. Giustiniano, Vincent Lenders","doi":"10.1145/2737095.2737124","DOIUrl":"https://doi.org/10.1145/2737095.2737124","url":null,"abstract":"Today's radio frequency (RF) spectrum measurements are mainly performed by governmental agencies which drive around using bulky and expensive specialized hardware. This approach does not scale well, providing us with only a poor situational awareness of the actual RF spectrum usage around us. We have developed a wideband spectrum monitoring sensor for remote operation that builds upon portable and low-cost commercial off-the-shelf (COTS) hardware components with a total cost per sensor device below $100. This results in a stunning cost reduction factor of 50 to 500 comparing to professional equipment. Our sensor platform adopts the software-defined radio paradigm and performs all signal processing steps on the CPU and GPU of a low-cost single-board computer. We address the challenges of large frequency errors and long scanning times due to the hardware constraints by proposing new correction and optimization methods, providing a satisfactory level of accuracy in indoor and outdoor environments. Our remote sensing platform is envisioned to be used at larger scale for various applications such as dynamic spectrum access in cognitive radios, detecting regions with elevated electro-smog, or for policy enforcement in the electromagnetic space.","PeriodicalId":318992,"journal":{"name":"Proceedings of the 14th International Conference on Information Processing in Sensor Networks","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114402541","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}