Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation最新文献

LightEQ: On-Device Earthquake Detection with Embedded Machine Learning LightEQ:基于嵌入式机器学习的设备地震检测

Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation Pub Date : 2023-05-09 DOI: 10.1145/3576842.3582387

Tayyaba Zainab, J. Karstens, O. Landsiedel

{"title":"LightEQ: On-Device Earthquake Detection with Embedded Machine Learning","authors":"Tayyaba Zainab, J. Karstens, O. Landsiedel","doi":"10.1145/3576842.3582387","DOIUrl":"https://doi.org/10.1145/3576842.3582387","url":null,"abstract":"The detection of earthquakes in seismological time series is central to observational seismology. Generally, seismic sensors passively record data and transmit it to the cloud or edge for integration, storage, and processing. However, transmitting raw data through the network is not an option for sensors deployed in harsh environments like underwater, underground, or in rural areas with limited connectivity. This paper introduces an efficient data processing pipeline and a set of lightweight deep-learning models for seismic event detection deployable on tiny devices such as microcontrollers. We conduct an extensive hyperparameter search and devise three lightweight models. We evaluate our models using the Stanford Earthquake Dataset and compare them with a basic STA/LTA detection algorithm and the state-of-the-art machine learning models, i.e., CRED, EQtransformer, and LCANet. For example, our smallest model consumes 193 kB of RAM and has an F1 score of 0.99 with just 29k parameters. Compared to CRED, which has an F1 score of 0.98 and 293k parameters, we reduce the number of parameters by a factor of 10. Deployed on Cortex M4 microcontrollers, the smallest version of LightEQ-NN has an inference time of 932 ms for 1 minute of raw data, an energy consumption of 5.86 mJ, and a flash requirement of 593 kB. Our results show that resource-efficient, on-device machine learning for seismological time series data is feasible and enables new approaches to seismic monitoring and early warning applications.","PeriodicalId":266438,"journal":{"name":"Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124587591","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}

引用次数: 1

A Knowledge Graph Question Answering Approach to IoT Forensics 物联网取证的知识图谱问答方法

Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation Pub Date : 2023-05-09 DOI: 10.1145/3576842.3589161

Ruipeng Zhang, Mengjun Xie

引用次数: 0

L-IDS: A lightweight hardware-assisted IDS for IoT systems to detect ransomware attacks L-IDS:用于物联网系统的轻量级硬件辅助IDS，用于检测勒索软件攻击

Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation Pub Date : 2023-05-09 DOI: 10.1145/3576842.3589170

Farhad Mofidi, Sena Hounsinou, Gedare Bloom

引用次数: 0

Handling Coexistence of LoRa with Other Networks through Embedded Reinforcement Learning 通过嵌入式强化学习处理LoRa与其他网络的共存

Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation Pub Date : 2023-05-09 DOI: 10.1145/3576842.3582383

Sezana Fahmida, Venkata Prashant Modekurthy‬, Mahbubur Rahman, Abusayeed Saifullah

{"title":"Handling Coexistence of LoRa with Other Networks through Embedded Reinforcement Learning","authors":"Sezana Fahmida, Venkata Prashant Modekurthy‬, Mahbubur Rahman, Abusayeed Saifullah","doi":"10.1145/3576842.3582383","DOIUrl":"https://doi.org/10.1145/3576842.3582383","url":null,"abstract":"The rapid growth of various Low-Power Wide-Area Network (LPWAN) technologies in the limited spectrum brings forth the challenge of their coexistence. Today, LPWANs are not equipped to handle this impending challenge. It is difficult to employ sophisticated media access control protocol for low-power nodes. Coexistence handling for WiFi or traditional short-range wireless network will not work for LPWANs. Due to long range, their nodes can be subject to an unprecedented number of hidden nodes, requiring highly energy-efficient techniques to handle such coexistence. In this paper, we address the coexistence problem for LoRa, a leading LPWAN technology. To improve the performance of a LoRa network under coexistence with many independent networks, we propose the design of a novel embedded learning agent based on a lightweight reinforcement learning at LoRa nodes. This is done by developing a Q-learning framework while ensuring minimal memory and computation overhead at LoRa nodes. The framework exploits transmission acknowledgments as feedback from the network based on what a node makes transmission decisions. To our knowledge, this is the first Q-learning approach for handling coexistence of low-power networks. Considering various coexistence scenarios of a LoRa network, we evaluate our approach through experiments indoors and outdoors. The outdoor results show that our Q-learning approach on average achieves an improvement of 46% in packet reception rate while reducing energy consumption by 66% in a LoRa network. In indoor experiments, we have observed some coexistence scenarios where a current LoRa network loses all the packets while our approach enables 99% packet reception rate with up to 90% improvement in energy consumption.","PeriodicalId":266438,"journal":{"name":"Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130232574","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}

引用次数: 1

AI-based Simultaneous Audio Localization and Communication for Robots 基于人工智能的机器人同步音频定位与通信

Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation Pub Date : 2023-05-09 DOI: 10.1145/3576842.3582373

Amjad Yousef Mjaid, Venkatesh Prasad, Mees Jonker, Casper Van Der Horst, Lucan De Groot, S. Narayana

{"title":"AI-based Simultaneous Audio Localization and Communication for Robots","authors":"Amjad Yousef Mjaid, Venkatesh Prasad, Mees Jonker, Casper Van Der Horst, Lucan De Groot, S. Narayana","doi":"10.1145/3576842.3582373","DOIUrl":"https://doi.org/10.1145/3576842.3582373","url":null,"abstract":"Introducing Chirpy, a hardware module designed for swarm robots that enables them to locate each other and communicate through audio. With the help of its deep learning module (AudioLocNet), Chirpy is capable of performing localization in challenging environments, such as those with non-line-of-sight and reverb. To support concurrent transmission, Chirpy uses orthogonal audio chirps and has an audio message frame design that balances localization accuracy and communication speed. As a result, a swarm of robots equipped with Chirpies can on-the-fly construct a path (or a potential field) to a location of interest without the need for a map, making them ideal for tasks such as search and rescue missions. Our experiments show that Chirpy can decode messages from four concurrent transmissions with a Bit Error Rate (BER) of at a distance of 250 cm, and it can communicate at Signal-to-Noise Ratios (SNRs) as low as -32 dB while maintaining ≈ 0 BER. Furthermore, AudioLocNet demonstrates high accuracy in classifying the location of a transmitter, even in adverse conditions such as non-line-of-sight and reverberant environments.","PeriodicalId":266438,"journal":{"name":"Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134014812","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}

引用次数: 0

Poster Abstract: SmartAppZoo: a Repository of SmartThings Apps for IoT Benchmarking 摘要:SmartAppZoo:一个用于物联网基准测试的智能物联网应用库

Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation Pub Date : 2023-05-09 DOI: 10.1145/3576842.3589162

Zhaohui Wang, B. Luo, Fengjun Li

引用次数: 0

Poster Abstract: Implementing Dynamic User Equilibrium in a Scaled City Environment with Duckietown and SUMO 摘要:利用Duckietown和SUMO实现规模化城市环境中的动态用户平衡

Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation Pub Date : 2023-05-09 DOI: 10.1145/3576842.3589172

T. Carroll, A. Cheng

引用次数: 0

Boosting Reliability and Energy-Efficiency in Indoor LoRa 提高室内LoRa的可靠性和能效

Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation Pub Date : 2023-05-09 DOI: 10.1145/3576842.3582327

Mahbubur Rahman, Abusayeed Saifullah

{"title":"Boosting Reliability and Energy-Efficiency in Indoor LoRa","authors":"Mahbubur Rahman, Abusayeed Saifullah","doi":"10.1145/3576842.3582327","DOIUrl":"https://doi.org/10.1145/3576842.3582327","url":null,"abstract":"LoRa (Long Range) is a promising communication technology for enabling the next-generation indoor Internet of Things applications. Very few studies, however, have analyzed its performance indoors. Besides, these indoor studies investigate mostly the RSSI (received signal strength indicator) and SNR (signal-to-noise ratio) of the received packets at the gateway, which, as we show, may not unfold the poor performance of LoRa and its MAC (medium access control) protocol – LoRaWAN – indoors in terms of reliability and energy-efficiency. In this paper, we evaluate the performance of LoRaWAN and use its key insights to boost the reliability and energy-efficiency in indoor environments by proposing LoRaIN (LoRa Indoor Network), a new link-layer protocol that can be effectively used for indoor deployments. The approach to boosting the reliability and energy-efficiency in LoRaIN is underpinned by enabling constructive interference with specific timing requirements for different pairs of channel bandwidth and spreading factor and relaying precious acknowledgments to the end-devices with the assistance of several booster nodes. The booster nodes do not need any special capability and can be a subset of the LoRa end-devices. To our knowledge, LoRaIN is the first protocol for boosting reliability and energy-efficiency in indoor LoRa networks. We evaluate its performance in an indoor testbed consisting of one LoRaWAN gateway and 20 LoRaWAN end-devices. Our extensive evaluation shows that when 15% of the end-devices operate as booster nodes, the reliability at the gateway increases from 62% to 95%, and the end-devices are approximately 2.5x energy-efficient.","PeriodicalId":266438,"journal":{"name":"Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125951558","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}

引用次数: 2

Incremental Anomaly Detection with Guarantee in the Internet of Medical Things 医疗物联网中具有保障的增量异常检测

Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation Pub Date : 2023-05-09 DOI: 10.1145/3576842.3582374

Xiayan Ji, Hyonyoung Choi, O. Sokolsky, Insup Lee

{"title":"Incremental Anomaly Detection with Guarantee in the Internet of Medical Things","authors":"Xiayan Ji, Hyonyoung Choi, O. Sokolsky, Insup Lee","doi":"10.1145/3576842.3582374","DOIUrl":"https://doi.org/10.1145/3576842.3582374","url":null,"abstract":"The Internet of Medical Things (IoMT), aided by learning-enabled components, is becoming increasingly important in health monitoring. However, the IoMT-based system must be highly reliable since it directly interacts with the patients. One critical function for facilitating reliable IoMT is anomaly detection, which involves sending alerts when a medical device’s usage pattern deviates from normal behavior. Due to the safety-critical nature of IoMT, the anomaly detectors are expected to have consistently high accuracy and low error, ideally being bounded with a guarantee. Besides, since the IoMT-based system is non-stationary, the anomaly detector and the performance guarantee should adapt to the evolving data distributions. To tackle these challenges, we propose a framework for incremental anomaly detection in IoMT with a Probably Approximately Correct (PAC)-based two-sided guarantee, guided by a human-in-the-loop design to accommodate shifts in anomaly distributions. As a result, our framework can improve detection performance and provide a tight guarantee on False Alarm Rate (FAR) and Miss Alarm Rate (MAR). We demonstrate the effectiveness of our design using synthetic data and the real-world IoMT monitoring platform VitalCore.","PeriodicalId":266438,"journal":{"name":"Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128668133","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}

引用次数: 2

One Ring to Rule Them All: An Open Source Smartring Platform for Finger Motion Analytics and Healthcare Applications 一个戒指统治他们所有:一个开源的智能平台，用于手指运动分析和医疗保健应用

Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation Pub Date : 2023-05-09 DOI: 10.1145/3576842.3582382

Hao Zhou, Taiting Lu, Yilin Liu, Shijia Zhang, Runze Liu, Mahanth K. Gowda

{"title":"One Ring to Rule Them All: An Open Source Smartring Platform for Finger Motion Analytics and Healthcare Applications","authors":"Hao Zhou, Taiting Lu, Yilin Liu, Shijia Zhang, Runze Liu, Mahanth K. Gowda","doi":"10.1145/3576842.3582382","DOIUrl":"https://doi.org/10.1145/3576842.3582382","url":null,"abstract":"This paper presents OmniRing, an open-source smartring platform with IMU and PPG sensors for activity tracking and health analytics applications. Smartring platforms are on the rise because of comfortable wearing, with the market size expected to reach $92 million soon. Nevertheless, most existing platforms are either commercial and proprietary without details of software/hardware or use suboptimal PCB design resulting in bulky form factors, inconvenient for wearing in daily life. Towards bridging the gap, OmniRing presents an extensible design of a smartring with a miniature form factor, longer battery life, wireless communication, and water resistance so that users can wear it all the time. Towards this end, OmniRing exploits opportunities in SoC, and carefully integrates the sensing units with a microcontroller and BLE modules. The electronic components are integrated on both sides of a flexible PCB that is bent in the shape of a ring and enclosed in a flexible and waterproof case for smooth skin contact. The overall cost is under $25, with weight of 2.5g, and up to a week of battery life. Extensive usability surveys validate the comfort levels. To validate the sensing capabilities, we enable an application in 3D finger motion tracking. By extracting synthetic training data from public videos coupled with data augmentation to minimize the overhead of training data generation for a new platform, OmniRing designs a transformer-based model that exploits correlations across fingers and time to track 3D finger motion with an accuracy of 6.57mm. We also validate the use of PPG data from OmniRing for heart rate monitoring. We believe the platform can enable exciting applications in fitness tracking, metaverse, sports, and healthcare.","PeriodicalId":266438,"journal":{"name":"Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129736770","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}

引用次数: 1