Woohyeok Choi, Je-ho Oh, Taiwoo Park, Seongjun Kang, Miri Moon, Uichin Lee, Inseok Hwang, Junehwa Song
The unique aquatic nature of swimming makes it very difficult to use social or technical strategies to mitigate the tediousness of monotonous exercises. In this study, we propose MobyDick, a smartphone-based multi-player exergame designed to be used while swimming, in which a team of swimmers collaborate to hunt down a virtual monster. In this paper, we present a novel, holistic game design that takes into account both human factors and technical challenges. Firstly, we perform a comparative analysis of a variety of wireless networking technologies in the aquatic environment and identify various technical constraints on wireless networking. Secondly, we develop a single phone-based inertial and barometric stroke activity recognition system to enable precise, real-time game inputs. Thirdly, we carefully devise a multi-player interaction mode viable in the underwater environment highly limiting the abilities of human communication. Finally, we prototype MobyDick on waterproof off-the-shelf Android phones, and deploy it to real swimming pool environments (n = 8). Our qualitative analysis of user interview data reveals certain unique aspects of multi-player swimming games.
{"title":"MobyDick: an interactive multi-swimmer exergame","authors":"Woohyeok Choi, Je-ho Oh, Taiwoo Park, Seongjun Kang, Miri Moon, Uichin Lee, Inseok Hwang, Junehwa Song","doi":"10.1145/2668332.2668352","DOIUrl":"https://doi.org/10.1145/2668332.2668352","url":null,"abstract":"The unique aquatic nature of swimming makes it very difficult to use social or technical strategies to mitigate the tediousness of monotonous exercises. In this study, we propose MobyDick, a smartphone-based multi-player exergame designed to be used while swimming, in which a team of swimmers collaborate to hunt down a virtual monster. In this paper, we present a novel, holistic game design that takes into account both human factors and technical challenges. Firstly, we perform a comparative analysis of a variety of wireless networking technologies in the aquatic environment and identify various technical constraints on wireless networking. Secondly, we develop a single phone-based inertial and barometric stroke activity recognition system to enable precise, real-time game inputs. Thirdly, we carefully devise a multi-player interaction mode viable in the underwater environment highly limiting the abilities of human communication. Finally, we prototype MobyDick on waterproof off-the-shelf Android phones, and deploy it to real swimming pool environments (n = 8). Our qualitative analysis of user interview data reveals certain unique aspects of multi-player swimming games.","PeriodicalId":223777,"journal":{"name":"Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128922307","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}
Will Hedgecock, M. Maróti, Á. Lédeczi, P. Völgyesi, Rueben A. Banalagay
One of the primary limitations to widescale adoption of many of today's high-precision location-aware applications is the cost associated with achieving the levels of accuracy necessary for safe and reliable operation. We have developed a relative localization solution enabling centimeter-scale positioning of a network of mobile nodes. The success of this research in the relative sense can be coupled with the known locations of a set of stationary nodes as well as the computational power of the cloud to open the door for an absolute localization service, whereby base stations at well-known locations can be used to transform relative coordinates into absolute locations. We will demonstrate the current progress of our work via live walking and driving experiments in which observers in an exhibition hall can issue commands to walkers and drivers in the field and see the results of these commands as determined by our positioning system in real-time.
{"title":"PinPtr: a high-precision GPS cloud service","authors":"Will Hedgecock, M. Maróti, Á. Lédeczi, P. Völgyesi, Rueben A. Banalagay","doi":"10.1145/2668332.2668342","DOIUrl":"https://doi.org/10.1145/2668332.2668342","url":null,"abstract":"One of the primary limitations to widescale adoption of many of today's high-precision location-aware applications is the cost associated with achieving the levels of accuracy necessary for safe and reliable operation. We have developed a relative localization solution enabling centimeter-scale positioning of a network of mobile nodes. The success of this research in the relative sense can be coupled with the known locations of a set of stationary nodes as well as the computational power of the cloud to open the door for an absolute localization service, whereby base stations at well-known locations can be used to transform relative coordinates into absolute locations. We will demonstrate the current progress of our work via live walking and driving experiments in which observers in an exhibition hall can issue commands to walkers and drivers in the field and see the results of these commands as determined by our positioning system in real-time.","PeriodicalId":223777,"journal":{"name":"Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132256753","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. R. Reddy, T. Chattopadhyay, Kingshuk Chakravarty, Aniruddha Sinha
In this paper authors have proposed a person identification method independent of his position with respect to the input sensor. The proposed method works for various postures or states namely, standing, sitting, walking. This method initially identifies the person's state and separate SVM based models are used for person identification (PI) for each of these three above mentioned states.
{"title":"Person identification from arbitrary position and posture using kinect","authors":"V. R. Reddy, T. Chattopadhyay, Kingshuk Chakravarty, Aniruddha Sinha","doi":"10.1145/2668332.2668359","DOIUrl":"https://doi.org/10.1145/2668332.2668359","url":null,"abstract":"In this paper authors have proposed a person identification method independent of his position with respect to the input sensor. The proposed method works for various postures or states namely, standing, sitting, walking. This method initially identifies the person's state and separate SVM based models are used for person identification (PI) for each of these three above mentioned states.","PeriodicalId":223777,"journal":{"name":"Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132828298","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}
Rohan Banerjee, A. Choudhury, Aniruddha Sinha, A. Visvanathan
In this paper we propose to demonstrate a smart phone application, that estimates human blood pressure (BP) values from photoplethysmography (PPG) signal using Windkessel model. PPG signal is extracted from a video sequence of a user's index fingertip, acquired using smart phone camera. A set of time domain PPG features are used to estimate different lumped parameters of Windkessel model to simulate arterial BP. Under most of the cases, the application estimates systolic and diastolic BP values, within a range of ±10% of clinical measurement.
{"title":"HeartSense: smart phones to estimate blood pressure from photoplethysmography","authors":"Rohan Banerjee, A. Choudhury, Aniruddha Sinha, A. Visvanathan","doi":"10.1145/2668332.2668378","DOIUrl":"https://doi.org/10.1145/2668332.2668378","url":null,"abstract":"In this paper we propose to demonstrate a smart phone application, that estimates human blood pressure (BP) values from photoplethysmography (PPG) signal using Windkessel model. PPG signal is extracted from a video sequence of a user's index fingertip, acquired using smart phone camera. A set of time domain PPG features are used to estimate different lumped parameters of Windkessel model to simulate arterial BP. Under most of the cases, the application estimates systolic and diastolic BP values, within a range of ±10% of clinical measurement.","PeriodicalId":223777,"journal":{"name":"Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130214498","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}
Rijurekha Sen, Youngki Lee, Kasthuri Jayarajah, Archan Misra, R. Balan
Real-time monitoring of groups and their rich contexts will be a key building block for futuristic, group-aware mobile services. In this paper, we propose GruMon, a fast and accurate group monitoring system for dense and complex urban spaces. GruMon meets the performance criteria of precise group detection at low latencies by overcoming two critical challenges of practical urban spaces, namely (a) the high density of crowds, and (b) the imprecise location information available indoors. Using a host of novel features extracted from commodity smartphone sensors, GruMon can detect over 80% of the groups, with 97% precision, using 10 minutes latency windows, even in venues with limited or no location information. Moreover, in venues where location information is available, GruMon improves the detection latency by up to 20% using semantic information and additional sensors to complement traditional spatio-temporal clustering approaches. We evaluated GruMon on data collected from 258 shopping episodes from 154 real participants, in two large shopping complexes in Korea and Singapore. We also tested GruMon on a large-scale dataset from an international airport (containing ≈37K+ unlabelled location traces per day) and a live deployment at our university, and showed both GruMon's potential performance at scale and various scalability challenges for real-world dense environment deployments.
{"title":"GruMon: fast and accurate group monitoring for heterogeneous urban spaces","authors":"Rijurekha Sen, Youngki Lee, Kasthuri Jayarajah, Archan Misra, R. Balan","doi":"10.1145/2668332.2668340","DOIUrl":"https://doi.org/10.1145/2668332.2668340","url":null,"abstract":"Real-time monitoring of groups and their rich contexts will be a key building block for futuristic, group-aware mobile services. In this paper, we propose GruMon, a fast and accurate group monitoring system for dense and complex urban spaces. GruMon meets the performance criteria of precise group detection at low latencies by overcoming two critical challenges of practical urban spaces, namely (a) the high density of crowds, and (b) the imprecise location information available indoors. Using a host of novel features extracted from commodity smartphone sensors, GruMon can detect over 80% of the groups, with 97% precision, using 10 minutes latency windows, even in venues with limited or no location information. Moreover, in venues where location information is available, GruMon improves the detection latency by up to 20% using semantic information and additional sensors to complement traditional spatio-temporal clustering approaches. We evaluated GruMon on data collected from 258 shopping episodes from 154 real participants, in two large shopping complexes in Korea and Singapore. We also tested GruMon on a large-scale dataset from an international airport (containing ≈37K+ unlabelled location traces per day) and a live deployment at our university, and showed both GruMon's potential performance at scale and various scalability challenges for real-world dense environment deployments.","PeriodicalId":223777,"journal":{"name":"Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115648570","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}
Kasthuri Jayarajah, Rijurekha Sen, Youngki Lee, Shriguru Nayak, Archan Misra, R. Balan
Detecting the group context of an individual (i.e., whether an individual is alone or part of a group) in crowded public spaces, such as shopping malls, is an important goal with many practical applications. However, in crowded indoor spaces, understanding the group-dependent movement behavior is a non-trivial problem as: (1) detecting groups is hard as the density ensures that at any location, a large number of people are moving together, (2) location tracking in many real-world venues is either absent or not very accurate, and (3) indoor mobility models that take into account group attributes (such as group size) are rare. In this paper, we first introduce GruMon, a platform for near real-time group monitoring in dense, public spaces, and then demonstrate how the movement & residency properties of individuals are significantly affected when they are in groups.
{"title":"Group analytics and insights for public spaces","authors":"Kasthuri Jayarajah, Rijurekha Sen, Youngki Lee, Shriguru Nayak, Archan Misra, R. Balan","doi":"10.1145/2668332.2668375","DOIUrl":"https://doi.org/10.1145/2668332.2668375","url":null,"abstract":"Detecting the group context of an individual (i.e., whether an individual is alone or part of a group) in crowded public spaces, such as shopping malls, is an important goal with many practical applications. However, in crowded indoor spaces, understanding the group-dependent movement behavior is a non-trivial problem as: (1) detecting groups is hard as the density ensures that at any location, a large number of people are moving together, (2) location tracking in many real-world venues is either absent or not very accurate, and (3) indoor mobility models that take into account group attributes (such as group size) are rare. In this paper, we first introduce GruMon, a platform for near real-time group monitoring in dense, public spaces, and then demonstrate how the movement & residency properties of individuals are significantly affected when they are in groups.","PeriodicalId":223777,"journal":{"name":"Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115742893","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}
C. Liang, Kaifei Chen, B. Priyantha, Jie Liu, Feng Zhao
Network traffic prioritization is gaining attention in the WSN community, as more and more features are being integrated into sensor networks. Real-world deployment experience suggests that WSN brings new challenges to existing problems, such as resource constraints, low data-rate radios, and diverse application scenarios. We present the RushNet framework that prioritizes two common traffic patterns in multi-hop sensor networks: low-priority (LP) traffic that is large-volume but delay-tolerant, and high-priority (HP) traffic that is sporadic but latency-sensitive. RushNet achieves schedule-free and coordination-free delivery differentiations with the following features. First, RushNet works with most data collection protocols to deliver LP traffic. Second, RushNet leverages transmission power difference and radio capture effect to implement on-demand HP packet delivery with low overhead. Third, RushNet proposes a retrodiction technique to help nodes minimize the overhead of recovering LP packet loss due to concurrent HP traffic. We evaluate RushNet performance with micro-benchmarks and a crowdsourced office comfort monitoring deployment. The deployment results suggest RushNet can achieve a throughput close to network capacity, and deliver 98% of the HP packets with a latency of less than four seconds.
{"title":"RushNet: practical traffic prioritization for saturated wireless sensor networks","authors":"C. Liang, Kaifei Chen, B. Priyantha, Jie Liu, Feng Zhao","doi":"10.1145/2668332.2668341","DOIUrl":"https://doi.org/10.1145/2668332.2668341","url":null,"abstract":"Network traffic prioritization is gaining attention in the WSN community, as more and more features are being integrated into sensor networks. Real-world deployment experience suggests that WSN brings new challenges to existing problems, such as resource constraints, low data-rate radios, and diverse application scenarios. We present the RushNet framework that prioritizes two common traffic patterns in multi-hop sensor networks: low-priority (LP) traffic that is large-volume but delay-tolerant, and high-priority (HP) traffic that is sporadic but latency-sensitive. RushNet achieves schedule-free and coordination-free delivery differentiations with the following features. First, RushNet works with most data collection protocols to deliver LP traffic. Second, RushNet leverages transmission power difference and radio capture effect to implement on-demand HP packet delivery with low overhead. Third, RushNet proposes a retrodiction technique to help nodes minimize the overhead of recovering LP packet loss due to concurrent HP traffic. We evaluate RushNet performance with micro-benchmarks and a crowdsourced office comfort monitoring deployment. The deployment results suggest RushNet can achieve a throughput close to network capacity, and deliver 98% of the HP packets with a latency of less than four seconds.","PeriodicalId":223777,"journal":{"name":"Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128673739","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 present the design, implementation, and evaluation of AirCloud -- a novel client-cloud system for pervasive and personal air-quality monitoring at low cost. At the frontend, we create two types of Internet-connected particulate matter (PM2:5) monitors -- AQM and miniAQM, with carefully designed mechanical structures for optimal air-flow. On the cloud-side, we create an air-quality analytics engine that learn and create models of air-quality based on a fusion of sensor data. This engine is used to calibrate AQMs and mini-AQMs in real-time, and infer PM2:5 concentrations. We evaluate AirCloud using 5 months of data and 2 month of continuous deployment, and show that AirCloud is able to achieve good accuracies at much lower cost than previous solutions. We also show three real applications built on top of AirCloud by 3rd party developers to further demonstrate the value of our system.
{"title":"AirCloud: a cloud-based air-quality monitoring system for everyone","authors":"Yun Cheng, Xiucheng Li, Zhijun Li, Shouxu Jiang, Yilong Li, Ji Jia, Xiaofan Jiang","doi":"10.1145/2668332.2668346","DOIUrl":"https://doi.org/10.1145/2668332.2668346","url":null,"abstract":"We present the design, implementation, and evaluation of AirCloud -- a novel client-cloud system for pervasive and personal air-quality monitoring at low cost. At the frontend, we create two types of Internet-connected particulate matter (PM2:5) monitors -- AQM and miniAQM, with carefully designed mechanical structures for optimal air-flow. On the cloud-side, we create an air-quality analytics engine that learn and create models of air-quality based on a fusion of sensor data. This engine is used to calibrate AQMs and mini-AQMs in real-time, and infer PM2:5 concentrations. We evaluate AirCloud using 5 months of data and 2 month of continuous deployment, and show that AirCloud is able to achieve good accuracies at much lower cost than previous solutions. We also show three real applications built on top of AirCloud by 3rd party developers to further demonstrate the value of our system.","PeriodicalId":223777,"journal":{"name":"Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems","volume":"452 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114703221","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}
IoT browser is a useful tool for the Internet of Things (IoT), which provides a novel way for people to interact with daily life objects through the Internet. Comparing with traditional web browsing environment, IoT browsing environment has some distinctive features such as the way of interacting with the physical objects, the importance of spatial-temporal information of objects, and the necessity of resource reuse. In this demonstration, we present a prototype of a proposed IoT browsing system architecture with a semantic-based learning-capable middleware for IoT browser and demonstrate the applicability of the system in a browsing scenario. The learning scheme is able to suggest users the next possible events when the users design their own service flows through web interface. The prototype shows that with the help of the IoT browsing system, heterogeneous devices can cooperate with each other to provide IoT services.
{"title":"A browsing system with learning capability for internet of things","authors":"Wen-Tsuen Chen, Chih-Hang Wang, Yen-Ju Lai, Po-Yu Chen","doi":"10.1145/2668332.2668377","DOIUrl":"https://doi.org/10.1145/2668332.2668377","url":null,"abstract":"IoT browser is a useful tool for the Internet of Things (IoT), which provides a novel way for people to interact with daily life objects through the Internet. Comparing with traditional web browsing environment, IoT browsing environment has some distinctive features such as the way of interacting with the physical objects, the importance of spatial-temporal information of objects, and the necessity of resource reuse. In this demonstration, we present a prototype of a proposed IoT browsing system architecture with a semantic-based learning-capable middleware for IoT browser and demonstrate the applicability of the system in a browsing scenario. The learning scheme is able to suggest users the next possible events when the users design their own service flows through web interface. The prototype shows that with the help of the IoT browsing system, heterogeneous devices can cooperate with each other to provide IoT services.","PeriodicalId":223777,"journal":{"name":"Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128955150","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}
Xiaolong Zheng, Zhichao Cao, Jiliang Wang, Yuan He, Yunhao Liu
To save energy, wireless sensor networks often run in a low duty cycle mode, where the radios of sensor nodes are scheduled between ON and OFF states. For nodes to communicate with each other, Low Power Listening (LPL) and Low Power Probing (LPP) are two types of rendezvous mechanisms. Nodes with LPL or LPP rely on signal strength or probe packets to detect potential transmissions, and then keep the radio-on for communications. Unfortunately, in many cases, signal strength and probe packets are susceptible to interference, resulting in undesirable radio on time when the signal strength of interference is above a threshold or a probe packet is interfered. To address the issue, we propose ZiSense, an energy efficient rendezvous mechanism which is resilient to interference. Instead of checking the signal strength or decoding the probe packets, ZiSense detects the existence of ZigBee transmissions and wakes up nodes accordingly. On sensor nodes with limited information and resource, we carefully study and extract short-term features purely from the time-domain RSSI sequence, and design a rule-based approach to efficiently identify the existence of ZigBee. We theoretically analyze the benefit of ZiSense in different environments and implement a prototype in TinyOS with TelosB motes. We examine ZiSense performance under controlled interference and office environments. The evaluation results show that, compared with state-of-the-art rendezvous mechanisms, ZiSense significantly reduces the energy consumption.
{"title":"ZiSense: towards interference resilient duty cycling in wireless sensor networks","authors":"Xiaolong Zheng, Zhichao Cao, Jiliang Wang, Yuan He, Yunhao Liu","doi":"10.1145/2668332.2668334","DOIUrl":"https://doi.org/10.1145/2668332.2668334","url":null,"abstract":"To save energy, wireless sensor networks often run in a low duty cycle mode, where the radios of sensor nodes are scheduled between ON and OFF states. For nodes to communicate with each other, Low Power Listening (LPL) and Low Power Probing (LPP) are two types of rendezvous mechanisms. Nodes with LPL or LPP rely on signal strength or probe packets to detect potential transmissions, and then keep the radio-on for communications. Unfortunately, in many cases, signal strength and probe packets are susceptible to interference, resulting in undesirable radio on time when the signal strength of interference is above a threshold or a probe packet is interfered. To address the issue, we propose ZiSense, an energy efficient rendezvous mechanism which is resilient to interference. Instead of checking the signal strength or decoding the probe packets, ZiSense detects the existence of ZigBee transmissions and wakes up nodes accordingly. On sensor nodes with limited information and resource, we carefully study and extract short-term features purely from the time-domain RSSI sequence, and design a rule-based approach to efficiently identify the existence of ZigBee. We theoretically analyze the benefit of ZiSense in different environments and implement a prototype in TinyOS with TelosB motes. We examine ZiSense performance under controlled interference and office environments. The evaluation results show that, compared with state-of-the-art rendezvous mechanisms, ZiSense significantly reduces the energy consumption.","PeriodicalId":223777,"journal":{"name":"Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127524319","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：