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IEEE International Conference on Pervasive Computing and Communications (PerCom)
Date
February 2025
hEARt: Motion-resilient Heart Rate Monitoring with In-ear Microphones
Kayla-Jade Butkow;Ting Dang;Andrea Ferlini;Dong Ma;Cecilia Mascolo
2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2023,Page(s):200 - 209
Cited by: Papers (12)
With the soaring adoption of in-ear wearables, the research community has started investigating suitable in-ear heart rate (HR) detection systems. HR is a key physiological marker of cardiovascular health and physical fitness. Continuous and reliable HR monitoring with wearable devices has therefore gained increasing attention in recent years. Existing HR detection systems in wearables mainly rely...Show More
Exposing the CSI: A Systematic Investigation of CSI-based Wi-Fi Sensing Capabilities and Limitations
2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2023,Page(s):81 - 90
Cited by: Papers (12)
Thanks to the ubiquitous deployment of Wi-Fi hotspots, channel state information (CSI)-based Wi-Fi sensing can unleash game-changing applications in many fields, such as healthcare, security, and entertainment. However, despite one decade of active research on Wi-Fi sensing, most existing work only considers legacy IEEE 802.11n devices, often in particular and strictly-controlled environments. Wor...Show More
WiDeep: WiFi-based Accurate and Robust Indoor Localization System using Deep Learning
Moustafa Abbas;Moustafa Elhamshary;Hamada Rizk;Marwan Torki;Moustafa Youssef
2019 IEEE International Conference on Pervasive Computing and Communications (PerCom
Publication Year: 2019,Page(s):1 - 10
Cited by: Papers (212)
Robust and accurate indoor localization has been the goal of several research efforts over the past decade. Due to the ubiquitous availability of WiFi indoors, many indoor localization systems have been proposed relying on WiFi fingerprinting. However, due to the inherent noise and instability of the wireless signals, the localization accuracy usually degrades and is not robust to dynamic changes ...Show More
Is Your Kettle Smarter Than a Hacker? A Scalable Tool for Assessing Replay Attack Vulnerabilities on Consumer IoT Devices
Sara Lazzaro;Vincenzo De Angelis;Anna Maria Mandalari;Francesco Buccafurri
2024 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2024,Page(s):114 - 124
Cited by: Papers (7)
Consumer Internet of Things (IoT) devices often leverage the local network to communicate with the corresponding companion app or other devices. This has benefits in terms of efficiency since it offloads the cloud. ENISA and NIST security guidelines underscore the importance of enabling default local communication for safety and reliability. Indeed, an IoT device should continue to function in cas...Show More
DeepApnea: Deep Learning Based Sleep Apnea Detection Using Smartwatches
Zida Liu;Xianda Chen;Fenglong Ma;Julio Fernandez-Mendoza;Guohong Cao
2024 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2024,Page(s):206 - 216
Sleep apnea is a serious sleep disorder where patients have multiple extended pauses in breath during sleep. Although some portable or contactless sleep apnea detection systems have been proposed, none of them can achieve fine-grained sleep apnea detection without strict requirements on the device or environmental settings. To address this problem, we present DeepApnea, a deep learning based sleep...Show More
An Analysis of Adversarial Attacks and Defenses on Autonomous Driving Models
Yao Deng;Xi Zheng;Tianyi Zhang;Chen Chen;Guannan Lou;Miryung Kim
2020 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2020,Page(s):1 - 10
Cited by: Papers (91)
Nowadays, autonomous driving has attracted much attention from both industry and academia. Convolutional neural network (CNN) is a key component in autonomous driving, which is also increasingly adopted in pervasive computing such as smartphones, wearable devices, and IoT networks. Prior work shows CNN-based classification models are vulnerable to adversarial attacks. However, it is uncertain to w...Show More
LANDMARC: indoor location sensing using active RFID
Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003).
Publication Year: 2003,Page(s):407 - 415
Growing convergence among mobile computing devices and embedded technology sparks the development and deployment of "context-aware" applications, where location is the most essential context. We present LANDMARC, a location sensing prototype system that uses Radio Frequency Identification (RFID) technology for locating objects inside buildings. The major advantage of LANDMARC is that it improves t...Show More
Serverledge: Decentralized Function-as-a-Service for the Edge-Cloud Continuum
Gabriele Russo Russo;Tiziana Mannucci;Valeria Cardellini;Francesco Lo Presti
2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2023,Page(s):131 - 140
Cited by: Papers (16)
As the Function-as-a-Service (FaaS) paradigm enjoys growing popularity within Cloud-based systems, there is increasing interest in moving serverless functions towards the Edge, to better support geo-distributed and pervasive applications. However, enjoying both the reduced latency of Edge and the scalability of FaaS requires new architectures and implementations to cope with typical Edge challenge...Show More
Stitching Satellites to the Edge: Pervasive and Efficient Federated LEO Satellite Learning
2024 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2024,Page(s):80 - 89
Cited by: Papers (1)
In the ambitious realm of space AI, the integration of federated learning (FL) with low Earth orbit (LEO) satellite constellations holds immense promise. However, many challenges persist in terms of feasibility, learning efficiency, and convergence. These hurdles stem from the bottleneck in communication, characterized by sporadic and irregular connectivity between LEO satellites and ground statio...Show More
Furcifer: a Context Adaptive Middleware for Real-world Object Detection Exploiting Local, Edge, and Split Computing in the Cloud Continuum
Matteo Mendula;Paolo Bellavista;Marco Levorato;Sharon Ladron de Guevara Contreras
2024 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2024,Page(s):47 - 56
Modern real-time applications widely embed compute intense neural algorithms at their core. Current solutions to support such algorithms either deploy highly-optimized Deep Neural Networks at mobile devices or offload the execution of possibly larger higher-performance neural models to edge servers. While the former solution typically maps to higher energy consumption and lower performance, the la...Show More
On-body localization of wearable devices: An investigation of position-aware activity recognition
2016 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2016,Page(s):1 - 9
Cited by: Papers (184)
Human activity recognition using mobile device sensors is an active area of research in pervasive computing. In our work, we aim at implementing activity recognition approaches that are suitable for real life situations. This paper focuses on the problem of recognizing the on-body position of the mobile device which in a real world setting is not known a priori. We present a new real world data se...Show More
FedCLAR: Federated Clustering for Personalized Sensor-Based Human Activity Recognition
2022 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2022,Page(s):227 - 236
Cited by: Papers (15)
Sensor-based Human Activity Recognition (HAR) has been a hot topic in pervasive computing for several years mainly due to its applications in healthcare and well-being. Centralized supervised approaches reach very high recognition rates, but they incur privacy and scalability issues. Federated Learning (FL) has been recently proposed to mitigate these issues. Each subject only shares the weights o...Show More
Converting Your Thoughts to Texts: Enabling Brain Typing via Deep Feature Learning of EEG Signals
Xiang Zhang;Lina Yao;Quan Z. Sheng;Salil S. Kanhere;Tao Gu;Dalin Zhang
2018 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2018,Page(s):1 - 10
Cited by: Papers (58)
An electroencephalography (EEG) based Brain Computer Interface (BCI) enables people to communicate with the outside world by interpreting the EEG signals of their brains to interact with devices such as wheelchairs and intelligent robots. More specifically, motor imagery EEG (MI-EEG), which reflects a subject's active intent, is attracting increasing attention for a variety of BCI applications. Ac...Show More
End-to-End Multi-Modal Tiny-CNN for Cardiovascular Monitoring on Sensor Patches
Mustafa Fuad Rifet Ibrahim;Tunc Alkanat;Maurice Meijer;Alexander Schlaefer;Peer Stelldinger
2024 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2024,Page(s):18 - 24
Cited by: Papers (1)
The vast majority of cardiovascular diseases are avoidable or treatable by preventive measures and early de-tection. To efficiently detect early signs and risk factors, car-diovascular parameters can be monitored continuously with small sensor patches, which improve the comfort of patients. However, processing the sensor data is a challenging task with the demanding needs of robustness, reliabilit...Show More
EMGSense: A Low-Effort Self-Supervised Domain Adaptation Framework for EMG Sensing
Di Duan;Huanqi Yang;Guohao Lan;Tianxing Li;Xiaohua Jia;Weitao Xu
2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2023,Page(s):160 - 170
Cited by: Papers (6)
This paper presents EMGSense, a low-effort self-supervised domain adaptation framework for sensing applications based on Electromyography (EMG). EMGSense addresses one of the fundamental challenges in EMG cross-user sensing—the significant performance degradation caused by time-varying biological heterogeneity—in a low-effort (data-efficient and label-free) manner. To alleviate the burden of data ...Show More
Ultra Write: A Lightweight Continuous Gesture Input System with Ultrasonic Signals on COTS Devices
2024 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2024,Page(s):174 - 183
Due to the advantages of acoustic sensing such as device ubiquity, hands-free interaction and privacy security, acoustic-based gesture input techniques have gained extensive at-tention and many excellent works have been proposed. However, these works have the following shortcomings: high cost of system construction, non-continuous input, and degraded performance in cross-user scenarios. To overcom...Show More
Adopting User-Space Networking for DDS Message-Oriented Middleware
Vincent Bode;Carsten Trinitis;Martin Schulz;David Buettner;Tobias Preclik
2024 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2024,Page(s):36 - 46
Cited by: Papers (1)
Due to the flexibility it offers, publish-subscribe messaging middleware is a popular choice in Industrial IoT (IIoT) applications. The Data Distribution Service (DDS) is a widely used industry standard for these systems with a focus on versatility and extensibility, implemented by multiple vendors and present in myriad deployments across industries like aerospace, healthcare and industrial automa...Show More
PreActo: Efficient Cross-Camera Object Tracking System in Video Analytics Edge Computing
Thanh-Tung Nguyen;Si Young Jang;Boyan Kostadinov;Dongman Lee
2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2023,Page(s):101 - 110
Cited by: Papers (3)
Cross-camera real-time object tracking is one of the important, yet challenging applications of video analytics in edge computing environments. To provide accurate and efficient real-time tracking, a tracking target's future movements need to be predicted. Particularly, the destination camera and travel time of the target object are to be identified so that tracking duties can be handover-ed seaml...Show More
AnchorLoc: Large-Scale, Real-Time Visual Localisation Through Anchor Extraction and Detection
2024 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2024,Page(s):125 - 134
Pervasive Augmented Reality (AR) requires accurate pose registration of the device in real-time at a neighbourhood-to-city scale. At such a scale, most pose registration techniques suffer from exponential computational and storage costs and a significant data collection burden. This paper introduces AnchorLoc, a framework that relies on visual anchors (stable and highly recognisable visual element...Show More
MassNet: A Deep Learning Approach for Body Weight Extraction from A Single Pressure Image
Ziyu Wu;Quan Wan;Mingjie Zhao;Yi Ke;Yiran Fang;Zhen Liang;Fangting Xie;Jingyuan Cheng
2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2023,Page(s):180 - 189
Cited by: Papers (6)
Body weight, as an essential physiological trait, is of considerable significance in many applications like body management, rehabilitation, and drug dosing for patient-specific treatments. Previous works on the body weight estimation task are mainly vision-based, using 2D/3D, depth, or infrared images, facing problems in illumination, occlusions, and especially privacy issues. The pressure mappin...Show More
Early Detection of Driving Maneuvers for Proactive Congestion Prevention
Debasree Das;Shameek Bhattacharjee;Sandip Chakraborty;Bivas Mitra;Sajal K. Das
2024 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2024,Page(s):135 - 142
Road traffic congestion affects not only the commute delay but also a city's overall social, economic, and environmental growth. Existing approaches for road congestion mitigation primarily adopt a reactive approach by detecting congestion after it occurs and recommending alternate routes to the vehicles, which fails to prevent congestion cascading. In contrast, we propose a pervasive platform cal...Show More
Affective- NLI: Towards Accurate and Interpretable Personality Recognition in Conversation
2024 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2024,Page(s):184 - 193
Personality Recognition in Conversation (PRC) aims to identify the personality traits of speakers through textual dialogue content. It is essential for providing personalized services in various applications of Human-Computer Interaction (HCI), such as AI-based mental therapy and companion robots for the elderly. Most recent studies analyze the dialog content for personality classification yet ove...Show More
Privacy-preserving Pedestrian Tracking using Distributed 3D LiDARs
Masakazu Ohno;Riki Ukyo;Tatsuya Amano;Hamada Rizk;Hirozumi Yamaguchi
2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2023,Page(s):43 - 52
Cited by: Papers (15)
The growing demand for intelligent environments unleashes an extraordinary cycle of privacy-aware applications that makes individuals' life more comfortable and safe. Examples of these applications include pedestrian tracking systems in large areas. Although the ubiquity of camera-based systems, they are not a preferable solution due to the vulnerability of leaking the privacy of pedestrians. In t...Show More
Leveraging On-Board UAV Motion Estimation for Lightweight Macroscopic Crowd Identification
Khizar Anjum;Tahmeed Chowdhury;Sreeram Mandava;Benedetto Piccoli;Dario Pompili
2024 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2024,Page(s):11 - 17
This paper introduces a novel, lightweight, on-board approach to crowd pattern identification, ingeniously using the processes of existing video compression standards, particularly H.264 or MPEG-4. Piggy-backing on the H.264 video-encoding algorithm, we propose real-time crowd pattern recognition and identification methodologies that can identify macroscopic patterns in as low as 2 milliseconds on...Show More
Stratified Transfer Learning for Cross-domain Activity Recognition
Jindong Wang;Yiqiang Chen;Lisha Hu;Xiaohui Peng;Philip S. Yu
2018 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2018,Page(s):1 - 10
Cited by: Papers (158)
In activity recognition, it is often expensive and time-consuming to acquire sufficient activity labels. To solve this problem, transfer learning leverages the labeled samples from the source domain to annotate the target domain which has few or none labels. Existing approaches typically consider learning a global domain shift while ignoring the intra-affinity between classes, which will hinder th...Show More
Decentralized Landslide Disaster Prediction for Imbalanced and Distributed Data
2024 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2024,Page(s):143 - 150
Precise disaster prediction plays a critical role in saving lives. Traditional landslide prediction methods have predominantly relied on deep neural networks such as CNNs and LSTMs. However, these methods face two main challenges. The first is the class imbalance issue, as landslides are rare, disrupting the training process. The second challenge stems from decentralized data management, with vari...Show More
Ortho-CodeA: Orthogonal Codes Assisted Backscatter Multiple Access
2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2023,Page(s):171 - 179
Cited by: Papers (6)
The research on backscatter multiple access schemes has been an interesting topic. Existing schemes in the area of backscatter multiple access are not designed for specific applications, and leave out the contemplation of practical application requirements. In this paper, therefore, we present Ortho-CodeA, a backscatter multiple access scheme that targets indoor Internet of Things (IoT) applicatio...Show More
Masa: Responsive Multi-DNN Inference on the Edge
Bart Cox;Jeroen Galjaard;Amirmasoud Ghiassi;Robert Birke;Lydia Y. Chen
2021 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2021,Page(s):1 - 10
Cited by: Papers (13)
Deep neural networks (DNNs) are becoming the core components of many applications running on edge devices, especially for real time image-based analysis. Increasingly, multi-faced knowledge is extracted via executing multiple DNNs inference models, e.g., identifying objects, faces, and genders from images. The response times of multi-DNN highly affect users’ quality of experience and safety...Show More
Device-Free Multi-Person Indoor Localization Using the Change of ToF
Atsushi Nomura;Masato Sugasaki;Kota Tsubouchi;Nobuhiko Nishio;Masamichi Shimosaka
2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2023,Page(s):190 - 199
Cited by: Papers (1)
Indoor position information, which is difficult to obtain by GPS, can be used for various services and applications, thus indoor localization methods have been widely researched. Among them, device-free indoor localization does not require the target persons to possess a localization device, such as a smartphone, which can support the localization of all persons in the environment. Many methods us...Show More
A Federated Learning Aggregation Algorithm for Pervasive Computing: Evaluation and Comparison
2021 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2021,Page(s):1 - 10
Cited by: Papers (43)
Pervasive computing promotes the installation of connected devices in our living spaces in order to provide services. Two major developments have gained significant momentum recently: an advanced use of edge resources and the integration of machine learning techniques for engineering applications. This evolution raises major challenges, in particular related to the appropriate distribution of comp...Show More
Scheduled Spatial Sensing against Adversarial WiFi Sensing
2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2023,Page(s):91 - 100
WiFi sensing aims to utilize the changes in the Channel State Information (CSI) of WiFi signals due to the reflections from objects in the environment for sensing purposes. It uses machine learning classification models to predict physical actions being performed in a given environment (e.g., human activities such as walking, running). Thanks to the existing WiFi infrastructure in most indoor area...Show More
GymSkill: A personal trainer for physical exercises
Andreas Möller;Luis Roalter;Stefan Diewald;Johannes Scherr;Matthias Kranz;Nils Hammerla;Patrick Olivier;Thomas Plötz
2012 IEEE International Conference on Pervasive Computing and Communications
Publication Year: 2012,Page(s):213 - 220
We present GymSkill, a personal trainer for ubiquitous monitoring and assessment of physical activity using standard fitness equipment. The system records and analyzes exercises using the sensors of a personal smartphone attached to the gym equipment. Novel fine-grained activity recognition techniques based on pyramidal Principal Component Breakdown Analysis (PCBA) provide a quantitative analysis ...Show More
Never skip leg day: A novel wearable approach to monitoring gym leg exercises
Bo Zhou;Mathias Sundholm;Jingyuan Cheng;Heber Cruz;Paul Lukowicz
2016 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2016,Page(s):1 - 9
Cited by: Papers (40)
We present a wearable textile sensor system for monitoring muscle activity, leveraging surface pressure changes between the skin and an elastic sport support band. The sensor is based on an 8×16 element fabric resistive pressure sensing matrix of 1cm spatial resolution, which can be read out with 50fps refresh rate. We evaluate the system by monitoring leg muscles during leg workouts in a gym out ...Show More
Context-Aware Data and Task Placement in Edge Computing Environments
Martin Breitbach;Dominik Schäfer;Janick Edinger;Christian Becker
2019 IEEE International Conference on Pervasive Computing and Communications (PerCom
Publication Year: 2019,Page(s):1 - 10
Cited by: Papers (57)
Computationally intensive tasks of IoT applications can be offloaded to powerful devices in the edge. Code offloading reduces energy consumption and increases performance. However, applications that use face recognition, machine learning, or image rendering, rely on large amounts of data. The transfer of this data leads to latencies which contradicts the responsiveness required by many pervasive a...Show More
GuideBeacon: Beacon-based indoor wayfinding for the blind, visually impaired, and disoriented
2017 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2017,Page(s):121 - 130
There are currently few options for navigational aids for the blind and visually impaired (BVI) in large indoor spaces. Such indoor spaces can be difficult to navigate even for the general sighted population if they are disoriented due to unfamiliarity or other reasons. This paper presents an indoor wayfinding system called GuideBeacon for the blind, visually impaired, and disoriented (BVID) that ...Show More
A Study of Bluetooth Low Energy performance for human proximity detection in the workplace
Alessandro Montanari;Sarfraz Nawaz;Cecilia Mascolo;Kerstin Sailer
2017 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2017,Page(s):90 - 99
Cited by: Papers (73)
The ability to detect and distinguish interactions in the workplace can shed light over productivity, team work and on employees' use of space. Questionnaires and direct observations have often been used as mechanisms to identify office based interactions, however, these are either very time consuming, yield coarse grained information or do not scale to large numbers of people. Technology has been...Show More
Topology Formation in IEEE 802.15.4: Cluster-Tree Characterization
2008 Sixth Annual IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2008,Page(s):276 - 281
Cited by: Papers (29)
The IEEE 802.15.4 standard defines a set of procedures to set-up a Low-Rate Wireless Personal Area Network where nodes self-organize into a logical communication structure through which data can be routed, hop by hop, from sources to destinations. The network formation of the IEEE 802.15.4 does not impose constraints on the topology. The ZigBee Alliance uses the IEEE 802.15.4 layers to build a com...Show More
Dead reckoning from the pocket - An experimental study
2010 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2010,Page(s):162 - 170
Modern mobile phones enable absolute positioning based on GPS or WiFi. However, incremental positioning based on dead reckoning is an interesting source of complementary information, e.g., for indoor positioning or for filling in reception gaps. In the literature however, reasonable dead reckoning accuracies have been reported for fixed and typically a priori known device placements only, e.g., on...Show More
UR2M: Uncertainty and Resource-Aware Event Detection on Microcontrollers
Hong Jia;Young D. Kwon;Dong Mat;Nhat Pham;Lorena Qendro;Tam Vu;Cecilia Mascolo
2024 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2024,Page(s):1 - 10
Traditional machine learning techniques are prone to generating inaccurate predictions when confronted with shifts in the distribution of data between the training and testing phases. This vulnerability can lead to severe consequences, especially in applications such as mobile healthcare. Uncertainty estimation has the potential to mitigate this issue by assessing the reliability of a model's outp...Show More
Highly Responsive Batteryless System for Indoor Light Energy Harvesting Environments
2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2023,Page(s):111 - 120
Energy-neutral operation (ENO) aims to provide near-perpetual device operation using energy harvested from ambient environments. Existing ENO techniques, however, have two key problems. The batteries used in harvesting devices have inherently limited lifespans, and the device experiences a long cold-start time when charging the battery. In this paper, we propose a long-lasting and highly responsiv...Show More
Joint Estimation of the Distance and Relative Velocity of Obstacles via Smartphone Active Sound Sensing for Pedestrian Safety
2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2023,Page(s):32 - 42
In this study, we proposed a new method for pedestrian safety named ObsSense that estimates the distance and relative velocity of both static and mobile roadside obstacles using probing signals emitted by an off-the-shelf smartphone carried by a pedestrian. Sound-based estimation of the movement properties of an obstacle has been actively studied in pervasive computing, and generally provides the ...Show More
Deep Triplet Networks with Attention for Sensor-based Human Activity Recognition
2021 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2021,Page(s):1 - 10
Cited by: Papers (32)
One of the most significant challenges in Human Activity Recognition using wearable devices is inter-class similarities and subject heterogeneity. These problems lead to the difficulties in constructing robust feature representations that might negatively affect the quality of recognition. This study, for the first time, applies deep triplet networks with various triplet loss functions and mining ...Show More
CrowdMeter: Congestion Level Estimation in Railway Stations Using Smartphones
Moustafa Elhamshary;Moustafa Youssef;Akira Uchiyama;Hirozumi Yamaguchi;Teruo Higashino
2018 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2018,Page(s):1 - 12
Cited by: Papers (16)
We present CrowdMeter: a participatory system that leverages the sensed data collected from users' phones during their daily train commutes to gauge the real-time congestion level in railway stations. CrowdMeter tracks the passenger's position in the station as well as identifies her context (e.g., waiting for a train, buying a ticket) along her trajectory from the station's entrance to the train....Show More
Embracing Self-Powered Wireless Wearables for Smart Healthcare
2021 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2021,Page(s):1 - 7
Cited by: Papers (11)
We present Apollo, a self-powered wireless biochemical system that is wearable and can continuously monitor personal health states. It has three key enablers. First, we design an ultra-low-power Bluetooth backscatter module, which can effectively take BLE signals as excitations and transmit sensor data at high data rates to smartphones. Further, at the core of self-power management is a novel mult...Show More
SolAR: Energy Positive Human Activity Recognition using Solar Cells
Muhammad Moid Sandhu;Sara Khalifa;Kai Geissdoerfer;Raja Jurdak;Marius Portmann
2021 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2021,Page(s):1 - 10
Cited by: Papers (18)
The high power consumption of inertial activity sensors limits the battery lifetime of today’s wearable devices. Recent studies promise to extend the lifetime of wearable devices by translating kinetic energy from human movements into electrical energy while using the harvesting signal to replace conventional activity sensors. However, in human-centric applications, the amount of harvested ...Show More
iMove: Exploring Bio-Impedance Sensing for Fitness Activity Recognition
Mengxi Liu;Vitor Fortes Rey;Yu Zhang;Lala Shakti Swarup Ray;Bo Zhou;Paul Lukowicz
2024 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2024,Page(s):194 - 205
Cited by: Papers (1)
Automatic and precise fitness activity recognition can be beneficial in aspects from promoting a healthy lifestyle to personalized preventative healthcare. While IMUs are currently the prominent fitness tracking modality, through iMove, we show bio-impedence can help improve IMU-based fitness tracking through sensor fusion and contrastive learning. To evaluate our methods, we conducted an experime...Show More
Investigating Enhancements to Contrastive Predictive Coding for Human Activity Recognition
2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2023,Page(s):232 - 241
Cited by: Papers (12)
The dichotomy between the challenging nature of obtaining annotations for activities, and the more straightforward nature of data collection from wearables, has resulted in significant interest in the development of techniques that utilize large quantities of unlabeled data for learning representations. Contrastive Predictive Coding (CPC) is one such method, learning effective representations by l...Show More
BrainNet: Improving Brainwave-based Biometric Recognition with Siamese Networks
2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2023,Page(s):53 - 60
Cited by: Papers (2)
With the advent of consumer wearables that capture brain activity, the use of brainwaves to verify a user's identity has been proposed as a convenient alternative to passwords. While recent work on brain biometrics shows feasible performance, it falls short in considering practical applicability. We propose a new solution, BrainNet, which trains a Siamese Network to measure the similarity of two e...Show More
PA2BLO: Low-Power, Personalized Audio Badge
Hemanth Sabbella;Dulaj Sanjaya Weerakoon;Manoj Gulati;Archan Misra
2024 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2024,Page(s):154 - 163
Cited by: Papers (1)
We present the hardware design and software pipeline for an ultra-low power device, in the form factor of a wearable badge, that supports energy efficient sensing, processing and wireless transfer of human voice commands and interactions. The proposed system, called PA2BLO, is envisioned to support both: (a) real-time, scalable, authorized voice based interaction and control of devices and applian...Show More
SmartSPEC: Customizable Smart Space Datasets via Event-driven Simulations
Andrew Chio;Daokun Jiang;Peeyush Gupta;Georgios Bouloukakis;Roberto Yus;Sharad Mehrotra;Nalini Venkatasubramanian
2022 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Publication Year: 2022,Page(s):152 - 162
Cited by: Papers (8)
This paper presents SmartSPEC, an approach to generate customizable smart space datasets using sensorized spaces in which people and events are embedded. Smart space datasets are critical to design, deploy and evaluate robust systems and applications to ensure cost-effective operation and safety/-comfort/convenience of the space occupants. Often, real-world data is difficult to obtain due to the l...Show More
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