Wonjung Kim, Seungchul Lee, Youngjae Chang, Taegyeong Lee, Inseok Hwang, Junehwa Song
Public spaces are equipped with 'public actuators', e.g., HVAC, lighting fixtures, speakers, or streaming TV channels to ensure their visitors' comfort. However, many public actuators rarely allow the visitors to adjust their operation, limiting their utility and fairness across the visitors. Also, the social bar is often too high to speak up one's preference and attempt to change an actuator's operation. Social control and use of IoT devices is an underexplored new direction of research even with its huge potential and implication, but comes with high complexity and scale. This paper proposes a novel architecture, namely, Social Control-and-Use Architecture for IoT Devices, which provides a systematic view and an effective tool to handle the complication and intricacy in system design. It also proposes Hivemind, a first-of-a-kind system developed, upon the architecture, for sharing IoT-enabled actuators in a public space. It transforms an exclusively-controlled actuator in a public space into a true public actuator, supporting visitors to instantly participate in the democratic collective control. Also, a myriad of off-the-shelf actuators are easily incorporated without modification to their implementation. The field deployment of Hivemind shows its comprehensive service coverage as well as the users' approval on the democratic collective control of public actuators.
{"title":"Hivemind","authors":"Wonjung Kim, Seungchul Lee, Youngjae Chang, Taegyeong Lee, Inseok Hwang, Junehwa Song","doi":"10.1145/3458864.3466626","DOIUrl":"https://doi.org/10.1145/3458864.3466626","url":null,"abstract":"Public spaces are equipped with 'public actuators', e.g., HVAC, lighting fixtures, speakers, or streaming TV channels to ensure their visitors' comfort. However, many public actuators rarely allow the visitors to adjust their operation, limiting their utility and fairness across the visitors. Also, the social bar is often too high to speak up one's preference and attempt to change an actuator's operation. Social control and use of IoT devices is an underexplored new direction of research even with its huge potential and implication, but comes with high complexity and scale. This paper proposes a novel architecture, namely, Social Control-and-Use Architecture for IoT Devices, which provides a systematic view and an effective tool to handle the complication and intricacy in system design. It also proposes Hivemind, a first-of-a-kind system developed, upon the architecture, for sharing IoT-enabled actuators in a public space. It transforms an exclusively-controlled actuator in a public space into a true public actuator, supporting visitors to instantly participate in the democratic collective control. Also, a myriad of off-the-shelf actuators are easily incorporated without modification to their implementation. The field deployment of Hivemind shows its comprehensive service coverage as well as the users' approval on the democratic collective control of public actuators.","PeriodicalId":153361,"journal":{"name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129668655","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}
Leonardo Bonati, Salvatore D’oro, S. Basagni, T. Melodia
The cellular networking ecosystem is being radically transformed by openness, softwarization, and virtualization principles, which will steer NextG networks toward solutions running on "white box" infrastructures. Telco operators will be able to truly bring intelligence to the network, dynamically deploying and adapting its elements at run time according to current conditions and traffic demands. Deploying intelligent solutions for softwarized NextG networks, however, requires extensive prototyping and testing procedures, currently largely unavailable. To this aim, this paper introduces SCOPE, an open and softwarized prototyping platform for NextG systems. SCOPE is made up of: (i) A ready-to-use, portable open-source container for instantiating softwarized and programmable cellular network elements (e.g., base stations and users); (ii) an emulation module for diverse real-world deployments, channels and traffic conditions for testing new solutions; (iii) a data collection module for artificial intelligence and machine learning-based applications, and (iv) a set of open APIs for users to control network element functionalities in real time. Researchers can use SCOPE to test and validate NextG solutions over a variety of large-scale scenarios before implementing them on commercial infrastructures. We demonstrate the capabilities of SCOPE and its platform independence by prototyping exemplary cellular solutions in the controlled environment of Colosseum, the world's largest wireless network emulator. We then port these solutions to indoor and outdoor testbeds, namely, to Arena and POWDER, a PAWR platform.
{"title":"SCOPE: an open and softwarized prototyping platform for NextG systems","authors":"Leonardo Bonati, Salvatore D’oro, S. Basagni, T. Melodia","doi":"10.1145/3458864.3466863","DOIUrl":"https://doi.org/10.1145/3458864.3466863","url":null,"abstract":"The cellular networking ecosystem is being radically transformed by openness, softwarization, and virtualization principles, which will steer NextG networks toward solutions running on \"white box\" infrastructures. Telco operators will be able to truly bring intelligence to the network, dynamically deploying and adapting its elements at run time according to current conditions and traffic demands. Deploying intelligent solutions for softwarized NextG networks, however, requires extensive prototyping and testing procedures, currently largely unavailable. To this aim, this paper introduces SCOPE, an open and softwarized prototyping platform for NextG systems. SCOPE is made up of: (i) A ready-to-use, portable open-source container for instantiating softwarized and programmable cellular network elements (e.g., base stations and users); (ii) an emulation module for diverse real-world deployments, channels and traffic conditions for testing new solutions; (iii) a data collection module for artificial intelligence and machine learning-based applications, and (iv) a set of open APIs for users to control network element functionalities in real time. Researchers can use SCOPE to test and validate NextG solutions over a variety of large-scale scenarios before implementing them on commercial infrastructures. We demonstrate the capabilities of SCOPE and its platform independence by prototyping exemplary cellular solutions in the controlled environment of Colosseum, the world's largest wireless network emulator. We then port these solutions to indoor and outdoor testbeds, namely, to Arena and POWDER, a PAWR platform.","PeriodicalId":153361,"journal":{"name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130928308","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}
As smartphones and tablets have become ubiquitous, there is a growing demand for apps that can enable users to collaboratively use multiple mobile systems. We present Tap, a framework that makes it easy for users to dynamically compose collections of mobile systems and developers to write apps that make use of those impromptu collections. Tap users control the composition by simply tapping systems together for discovery and authentication. The physical interaction mimics and supports ephemeral user interactions without the need for tediously exchanging user contact information such as phone numbers or email addresses. Tapping triggers a simple NFC-based mechanism to exchange connectivity information and security credentials that works across heterogeneous networks and requires no user accounts or cloud infrastructure support. Tap makes it possible for apps to use existing mobile platform APIs across multiple mobile systems by virtualizing data sources so that local and remote data sources can be combined together upon tapping. Virtualized data sources can be hardware or software features, including media, clipboard, calendar events, and devices such as cameras and microphones. Leveraging existing mobile platform APIs makes it easy for developers to write apps that use hardware and software features across dynamically composed collections of mobile systems. We have implemented a Tap prototype that allows apps to make use of both unmodified Android and iOS systems. We have modified and implemented various apps using Tap to demonstrate that it is easy to use and can enable apps to provide powerful new functionality by leveraging multiple mobile systems. Our results show that Tap has good performance, even for high-bandwidth features, and is user and developer friendly.
{"title":"Tap: an app framework for dynamically composable mobile systems","authors":"Naser AlDuaij, Jason Nieh","doi":"10.1145/3458864.3467678","DOIUrl":"https://doi.org/10.1145/3458864.3467678","url":null,"abstract":"As smartphones and tablets have become ubiquitous, there is a growing demand for apps that can enable users to collaboratively use multiple mobile systems. We present Tap, a framework that makes it easy for users to dynamically compose collections of mobile systems and developers to write apps that make use of those impromptu collections. Tap users control the composition by simply tapping systems together for discovery and authentication. The physical interaction mimics and supports ephemeral user interactions without the need for tediously exchanging user contact information such as phone numbers or email addresses. Tapping triggers a simple NFC-based mechanism to exchange connectivity information and security credentials that works across heterogeneous networks and requires no user accounts or cloud infrastructure support. Tap makes it possible for apps to use existing mobile platform APIs across multiple mobile systems by virtualizing data sources so that local and remote data sources can be combined together upon tapping. Virtualized data sources can be hardware or software features, including media, clipboard, calendar events, and devices such as cameras and microphones. Leveraging existing mobile platform APIs makes it easy for developers to write apps that use hardware and software features across dynamically composed collections of mobile systems. We have implemented a Tap prototype that allows apps to make use of both unmodified Android and iOS systems. We have modified and implemented various apps using Tap to demonstrate that it is easy to use and can enable apps to provide powerful new functionality by leveraging multiple mobile systems. Our results show that Tap has good performance, even for high-bandwidth features, and is user and developer friendly.","PeriodicalId":153361,"journal":{"name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","volume":"15 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121315289","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}
Joe Breen, Jonathon Duerig, E. Eide, Mike Hibler, David Johnson, S. Kasera, Dustin Maas, Alex Orange, Neal Patwari, R. Ricci, D. Schurig, L. Stoller, J. Merwe, Kirk Webb, Gary Wong
POWDER is a highly flexible, deeply programmable, and city-scale scientific instrument that enables cutting-edge research in wireless technologies. Researchers interact with the POWDER platform via the Internet to conduct their experiments, with zero penalty for remote access. In this two-part demonstration, the POWDER implementers show how to use the platform. First, they present the workflow that researchers follow to conduct experiments. Second, they highlight some of the hardware and software building blocks available through POWDER, including components related to over-the-air wireless and mobile networking, 5G, and massive MIMO.
{"title":"Mobile and wireless research on the POWDER platform","authors":"Joe Breen, Jonathon Duerig, E. Eide, Mike Hibler, David Johnson, S. Kasera, Dustin Maas, Alex Orange, Neal Patwari, R. Ricci, D. Schurig, L. Stoller, J. Merwe, Kirk Webb, Gary Wong","doi":"10.1145/3458864.3466915","DOIUrl":"https://doi.org/10.1145/3458864.3466915","url":null,"abstract":"POWDER is a highly flexible, deeply programmable, and city-scale scientific instrument that enables cutting-edge research in wireless technologies. Researchers interact with the POWDER platform via the Internet to conduct their experiments, with zero penalty for remote access. In this two-part demonstration, the POWDER implementers show how to use the platform. First, they present the workflow that researchers follow to conduct experiments. Second, they highlight some of the hardware and software building blocks available through POWDER, including components related to over-the-air wireless and mobile networking, 5G, and massive MIMO.","PeriodicalId":153361,"journal":{"name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129418982","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}
Alejandro Blanco Pizarro, J. P. Beltran, Marco Cominelli, F. Gringoli, Joerg Widmer
WiFi location systems are remarkably accurate, with decimeter-level errors for recent CSI-based systems. However, such high accuracy is achieved under Line-of-Sight (LOS) conditions and with an access point (AP) density that is much higher than that typically found in current deployments that primarily target good coverage. In contrast, when many of the APs within range are in Non-Line-of-Sight (NLOS), the location accuracy degrades drastically. In this paper we present UbiLocate, a WiFi location system that copes well with common AP deployment densities and works ubiquitously, i.e., without excessive degradation under NLOS. UbiLocate demonstrates that meter-level median accuracy NLOS localization is possible through (i) an innovative angle estimator based on a Nelder-Mead search, (ii) a fine-grained time of flight ranging system with nanosecond resolution, and (iii) the accuracy improvements brought about by the increase in bandwidth and number of antennas of IEEE 802.11ac. In combination, they provide superior resolvability of multipath components, significantly improving location accuracy over prior work. We implement our location system on off-the-shelf 802.11ac devices and make the implementation, CSI-extraction tool and custom Fine Timing Measurement design publicly available to the research community. We carry out an extensive performance analysis of our system and show that it outperforms current state-of-the-art location systems by a factor of 2--3, both under LOS and NLOS.
{"title":"Accurate ubiquitous localization with off-the-shelf IEEE 802.11ac devices","authors":"Alejandro Blanco Pizarro, J. P. Beltran, Marco Cominelli, F. Gringoli, Joerg Widmer","doi":"10.1145/3458864.3468850","DOIUrl":"https://doi.org/10.1145/3458864.3468850","url":null,"abstract":"WiFi location systems are remarkably accurate, with decimeter-level errors for recent CSI-based systems. However, such high accuracy is achieved under Line-of-Sight (LOS) conditions and with an access point (AP) density that is much higher than that typically found in current deployments that primarily target good coverage. In contrast, when many of the APs within range are in Non-Line-of-Sight (NLOS), the location accuracy degrades drastically. In this paper we present UbiLocate, a WiFi location system that copes well with common AP deployment densities and works ubiquitously, i.e., without excessive degradation under NLOS. UbiLocate demonstrates that meter-level median accuracy NLOS localization is possible through (i) an innovative angle estimator based on a Nelder-Mead search, (ii) a fine-grained time of flight ranging system with nanosecond resolution, and (iii) the accuracy improvements brought about by the increase in bandwidth and number of antennas of IEEE 802.11ac. In combination, they provide superior resolvability of multipath components, significantly improving location accuracy over prior work. We implement our location system on off-the-shelf 802.11ac devices and make the implementation, CSI-extraction tool and custom Fine Timing Measurement design publicly available to the research community. We carry out an extensive performance analysis of our system and show that it outperforms current state-of-the-art location systems by a factor of 2--3, both under LOS and NLOS.","PeriodicalId":153361,"journal":{"name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122053579","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}
Seyeon Kim, Kyungmin Bin, Sangtae Ha, Kyunghan Lee, S. Chong
DVFS (dynamic voltage and frequency scaling) is a system-level technique that adjusts voltage and frequency levels of CPU/GPU at runtime to balance energy efficiency and high performance. DVFS has been studied for many years, but it is considered still challenging to realize a DVFS that performs ideally for mobile devices for two main reasons: i) an optimal power budget distribution between CPU and GPU in a power-constrained platform can only be defined by the application performance, but conventional DVFS implementations are mostly application-agnostic; ii) mobile platforms experience dynamic thermal environments for many reasons such as mobility and holding methods, but conventional implementations are not adaptive enough to such environmental changes. In this work, we propose a deep reinforcement learning-based frequency scaling technique, zTT. zTT learns thermal environmental characteristics and jointly scales CPU and GPU frequencies to maximize the application performance in an energy-efficient manner while achieving zero thermal throttling. Our evaluations for zTT implemented on Google Pixel 3a and NVIDIA JETSON TX2 platform with various applications show that zTT can adapt quickly to changing thermal environments, consistently resulting in high application performance with energy efficiency. In a high-temperature environment where a rendering application with the default mobile DVFS fails to keep producing more than a target frame rate, zTT successfully manages to do so even with 23.9% less average power consumption.
{"title":"zTT: learning-based DVFS with zero thermal throttling for mobile devices","authors":"Seyeon Kim, Kyungmin Bin, Sangtae Ha, Kyunghan Lee, S. Chong","doi":"10.1145/3458864.3468161","DOIUrl":"https://doi.org/10.1145/3458864.3468161","url":null,"abstract":"DVFS (dynamic voltage and frequency scaling) is a system-level technique that adjusts voltage and frequency levels of CPU/GPU at runtime to balance energy efficiency and high performance. DVFS has been studied for many years, but it is considered still challenging to realize a DVFS that performs ideally for mobile devices for two main reasons: i) an optimal power budget distribution between CPU and GPU in a power-constrained platform can only be defined by the application performance, but conventional DVFS implementations are mostly application-agnostic; ii) mobile platforms experience dynamic thermal environments for many reasons such as mobility and holding methods, but conventional implementations are not adaptive enough to such environmental changes. In this work, we propose a deep reinforcement learning-based frequency scaling technique, zTT. zTT learns thermal environmental characteristics and jointly scales CPU and GPU frequencies to maximize the application performance in an energy-efficient manner while achieving zero thermal throttling. Our evaluations for zTT implemented on Google Pixel 3a and NVIDIA JETSON TX2 platform with various applications show that zTT can adapt quickly to changing thermal environments, consistently resulting in high application performance with energy efficiency. In a high-temperature environment where a rendering application with the default mobile DVFS fails to keep producing more than a target frame rate, zTT successfully manages to do so even with 23.9% less average power consumption.","PeriodicalId":153361,"journal":{"name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122121079","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}
Pub Date : 2021-06-24DOI: 10.1002/0471684228.egp12331
Naser AlDuaij, Jason Nieh
{"title":"Tap","authors":"Naser AlDuaij, Jason Nieh","doi":"10.1002/0471684228.egp12331","DOIUrl":"https://doi.org/10.1002/0471684228.egp12331","url":null,"abstract":"","PeriodicalId":153361,"journal":{"name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124248020","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}
Seyed Mohammadjavad Seyed Talebi, A. A. Sani, S. Saroiu, A. Wolman
Voice assistants raise serious security and privacy concerns because they use always-on microphones in sensitive locations (e.g., inside a home) and send audio recordings to the cloud for processing. The cloud transcribes these recordings and interprets them as user requests, and sometimes even shares these requests with third-party services. These steps may result in unintended or malicious voice data leaks and in unauthorized actions, such as a purchase. This paper presents MegaMind, a novel extensible platform that lets a user deploy security and privacy extensions locally on their voice assistant. MegaMind's extensions interpose on requests before sending them to the cloud and on responses before delivering them to the user. MegaMind's programming model enables writing powerful extensions with ease, such as one for secure conversations. Additionally, MegaMind protects against malicious extensions by providing two important guarantees, namely permission enforcement and non-interference. We implement MegaMind and integrate it with Amazon Alexa Service SDK. Our evaluation shows that MegaMind achieves a small conversation latency on platforms with adequate compute power, such as a Raspberry Pi 4 and an x86-based laptop.
{"title":"MegaMind","authors":"Seyed Mohammadjavad Seyed Talebi, A. A. Sani, S. Saroiu, A. Wolman","doi":"10.1145/3458864.3467962","DOIUrl":"https://doi.org/10.1145/3458864.3467962","url":null,"abstract":"Voice assistants raise serious security and privacy concerns because they use always-on microphones in sensitive locations (e.g., inside a home) and send audio recordings to the cloud for processing. The cloud transcribes these recordings and interprets them as user requests, and sometimes even shares these requests with third-party services. These steps may result in unintended or malicious voice data leaks and in unauthorized actions, such as a purchase. This paper presents MegaMind, a novel extensible platform that lets a user deploy security and privacy extensions locally on their voice assistant. MegaMind's extensions interpose on requests before sending them to the cloud and on responses before delivering them to the user. MegaMind's programming model enables writing powerful extensions with ease, such as one for secure conversations. Additionally, MegaMind protects against malicious extensions by providing two important guarantees, namely permission enforcement and non-interference. We implement MegaMind and integrate it with Amazon Alexa Service SDK. Our evaluation shows that MegaMind achieves a small conversation latency on platforms with adequate compute power, such as a Raspberry Pi 4 and an x86-based laptop.","PeriodicalId":153361,"journal":{"name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126380682","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}
Wonjung Kim, Seungchul Lee, Youngjae Chang, Taegyeong Lee, Inseok Hwang, Junehwa Song
Public spaces, where we gather, commune, and take a rest, are the essential parts of a modern urban landscape, enriching citizen's everyday life [3]. How we share these spaces are considered an indicator of the quality of life. Public spaces thus have a responsibility to provide comfort and satisfaction to any visitors. However, in most times, the operations of the spaces are managed in rather an exclusive manner.
{"title":"Facilitating in-situ shared use of IoT actuators in public spaces","authors":"Wonjung Kim, Seungchul Lee, Youngjae Chang, Taegyeong Lee, Inseok Hwang, Junehwa Song","doi":"10.1145/3458864.3468444","DOIUrl":"https://doi.org/10.1145/3458864.3468444","url":null,"abstract":"Public spaces, where we gather, commune, and take a rest, are the essential parts of a modern urban landscape, enriching citizen's everyday life [3]. How we share these spaces are considered an indicator of the quality of life. Public spaces thus have a responsibility to provide comfort and satisfaction to any visitors. However, in most times, the operations of the spaces are managed in rather an exclusive manner.","PeriodicalId":153361,"journal":{"name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116975520","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 paper, we present RFDiaper, a commodity passive RFID based healthy diapering system, which can sense the diaper wetness (i.e., wet/dry) and identify pH value of urine absorbed by the diaper. To do so, we leverage the coupling effect between the urine absorbed by the diaper and RFID tag, thereby the phase and amplitude variation can indicate urine pH and diaper wetness. However, rich scattering and dynamic environment exhibit a great challenge for accurate diaper wetness sensing and urine pH identification. Therefore, we propose a twin-tag based dynamic environment mitigation approach for robust and healthy diapering. Specifically, by extracting the differential amplitude and phase from the co-located sensing tag and reference tag (i.e., twin-tag) attached on the diaper, the multipath effect and the other dynamic factors (e.g., diaper wearer's body, tag's orientation and temperature, etc.) can be mitigated. Then, we detect the diaper wetness and estimate the urine pH based on differential amplitude and phase. We have implemented RFDiaper's design and evaluated its effectiveness with the experiments using commercial off-the-shelf (COTS) RFID tags attached on the diaper worn by the doll and the human subjects. RFDiaper can achieve the median accuracy of around 96% for diaper wetness sensing and urine pH estimation error of around 0.23 in dynamic environment.
{"title":"Healthy diapering with passive RFIDs for diaper wetness sensing and urine pH identification","authors":"Wei Sun, K. Srinivasan","doi":"10.1145/3458864.3466870","DOIUrl":"https://doi.org/10.1145/3458864.3466870","url":null,"abstract":"In this paper, we present RFDiaper, a commodity passive RFID based healthy diapering system, which can sense the diaper wetness (i.e., wet/dry) and identify pH value of urine absorbed by the diaper. To do so, we leverage the coupling effect between the urine absorbed by the diaper and RFID tag, thereby the phase and amplitude variation can indicate urine pH and diaper wetness. However, rich scattering and dynamic environment exhibit a great challenge for accurate diaper wetness sensing and urine pH identification. Therefore, we propose a twin-tag based dynamic environment mitigation approach for robust and healthy diapering. Specifically, by extracting the differential amplitude and phase from the co-located sensing tag and reference tag (i.e., twin-tag) attached on the diaper, the multipath effect and the other dynamic factors (e.g., diaper wearer's body, tag's orientation and temperature, etc.) can be mitigated. Then, we detect the diaper wetness and estimate the urine pH based on differential amplitude and phase. We have implemented RFDiaper's design and evaluated its effectiveness with the experiments using commercial off-the-shelf (COTS) RFID tags attached on the diaper worn by the doll and the human subjects. RFDiaper can achieve the median accuracy of around 96% for diaper wetness sensing and urine pH estimation error of around 0.23 in dynamic environment.","PeriodicalId":153361,"journal":{"name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125966689","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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