Proceedings of the 8th International Conference on the Internet of Things最新文献_第5页

Towards designing open and secure IoT systems: insights for practitioners 面向设计开放和安全的物联网系统:从业者的见解

Proceedings of the 8th International Conference on the Internet of Things Pub Date : 2018-10-15 DOI: 10.1145/3277593.3277615

Bahtijar Vogel, Rimpu Varshney

引用次数: 6

On efficient resource allocation in the internet of things environment 论物联网环境下资源的高效配置

Proceedings of the 8th International Conference on the Internet of Things Pub Date : 2018-10-15 DOI: 10.1145/3277593.3277623

Sheheeda Manakkadu, S. Dutta

引用次数: 3

Mining channel state information from bluetooth low energy RSSI for robust object-to-object ranging 从蓝牙低能量RSSI中挖掘通道状态信息，实现鲁棒的目标到目标测距

Proceedings of the 8th International Conference on the Internet of Things Pub Date : 2018-10-15 DOI: 10.1145/3277593.3277624

Rahul Majethia, K. Rajkumar

{"title":"Mining channel state information from bluetooth low energy RSSI for robust object-to-object ranging","authors":"Rahul Majethia, K. Rajkumar","doi":"10.1145/3277593.3277624","DOIUrl":"https://doi.org/10.1145/3277593.3277624","url":null,"abstract":"In the world of smart objects, device-ranging and localization using Bluetooth Low Energy (BLE) is becoming popular due to its attractive energy performance, wide platform support and low costs. There has been sufficient motivation on statistical analysis of Channel State Information of Received Signal Strength Indicator (RSSI) data for more effective ranging-based models. However, there has been no ubiquitous solution which is both receiver-agnostic and does not require alteration in the advertisement protocol or packet structure of BLE. In this paper, we propose a truly unsupervised approach for channel-annotation of RSSI data received by a stationary receiver object. Given a sequence of RSSI observations and a discoverable receiver channel-switching policy, we determine the period and hence the time spent by the receiver in an individual channel. Then, we propose a sliding-window based algorithm which utilizes two well-established Likelihood-Ratio algorithms - KLIEP and uLSIF - for extracting Channel State Information of retrospective RSSI observation data. We believe this work lays the foundation of motivating future work in completely unsupervised methods for object-to-object ranging and localization.","PeriodicalId":129822,"journal":{"name":"Proceedings of the 8th International Conference on the Internet of Things","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124139252","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: 7

Latency-aware decentralized resource management for IoT applications 物联网应用程序的延迟感知分散资源管理

Proceedings of the 8th International Conference on the Internet of Things Pub Date : 2018-10-15 DOI: 10.1145/3277593.3277637

Cosmin Avasalcai, S. Dustdar

引用次数: 6

Methodology for forecasting user experience for smart and assisted living in affect aware systems 在影响感知系统中预测智能和辅助生活的用户体验的方法

Proceedings of the 8th International Conference on the Internet of Things Pub Date : 2018-10-15 DOI: 10.1145/3277593.3277630

Nirmalya Thakur, C. Han

引用次数: 13

Speech recognition and voice separation for the internet of things 物联网语音识别和语音分离

Proceedings of the 8th International Conference on the Internet of Things Pub Date : 2018-10-15 DOI: 10.1145/3277593.3277610

M. Hasanzadeh-Mofrad, D. Mossé

{"title":"Speech recognition and voice separation for the internet of things","authors":"M. Hasanzadeh-Mofrad, D. Mossé","doi":"10.1145/3277593.3277610","DOIUrl":"https://doi.org/10.1145/3277593.3277610","url":null,"abstract":"Internet-connected home automation devices like Amazon Echo, Nest Thermostat and smart TVs are riding the wave of the Internet of Things (IoT). The most intuitive, natural and efficient way to communicate with these devices is through talking with them (via voice commands). Speech recognition provides the medium to process and convert spoken language to plain text for further use of the system. Current personal assistants like Amazon Echo and Google Home have been designed for home automation, impacting billions of people's lives; yet, they are not customizable. Another limitation of these devices is that they cannot recognize concurrent voice commands issued by two persons at the same time. We tackle this last challenge, given that often there is more than one person in each room. The contributions of this paper are twofold: (1) we build an inexpensive and customizable voice-enabled IoT prototype using Raspberry Pi motherboard and Google Cloud speech-to-text API and (2) we propose a method to solve the problem of voice separation in the context of IoT when two people are trying to send commands to a voice-enabled IoT device and both commands are required to be processed and executed simultaneously. Using our proposed voice separation approach, our results showed that we improved the accuracy of transcription process up to 3% compared to the baseline model which does not support for voice separation.","PeriodicalId":129822,"journal":{"name":"Proceedings of the 8th International Conference on the Internet of Things","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131528822","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: 10

RDF4Led RDF4Led

Proceedings of the 8th International Conference on the Internet of Things Pub Date : 2018-10-15 DOI: 10.1145/3277593.3277600

Anh Le-Tuan, Conor Hayes, Marcin Wylot, Danh Le-Phuoc

{"title":"RDF4Led","authors":"Anh Le-Tuan, Conor Hayes, Marcin Wylot, Danh Le-Phuoc","doi":"10.1145/3277593.3277600","DOIUrl":"https://doi.org/10.1145/3277593.3277600","url":null,"abstract":"Semantic interoperability for the Internet of Things(IoT) is being enabled by standards and technologies from the Semantic Web. As recent research suggests a move towards decentralised IoT architectures, our focus is on how to enable scalable and robust RDF engines that can be embedded throughout the architecture, in particular at edge nodes. RDF processing at edge enables the creation of semantic integration gateways for locally connected low-level devices. We introduce a lightweight RDF engine, which comprises of RDF storage and SPARQL processor, for the lightweight edge devices, called RDF4Led. RDF4Led follows the RISCstyle (Reduce Instruction Set Computer) design philosophy. The design comprises a flash-aware storage structure, an indexing scheme and a low-memory-footprint join algorithm which improves scalability as well as robustness over competing solutions. With a significantly smaller memory footprint, we show that RDF4Led can handle 2 to 5 times more data than RDF engines such as Jena TDB and Virtuoso. On three types of ARM boards, RDF4Led requires 10--30% memory of its competitors to operate up to 30 million triples dataset; it can perform faster updates and can scale better than Jena TDB and Virtuoso. Furthermore, we demonstrate considerably faster query operations than Jena TDB.","PeriodicalId":129822,"journal":{"name":"Proceedings of the 8th International Conference on the Internet of Things","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128418058","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: 14

A multi-step and resilient predictive Q-learning algorithm for IoT: a case study in water supply networks 面向物联网的多步骤弹性预测q学习算法:供水网络案例研究

Proceedings of the 8th International Conference on the Internet of Things Pub Date : 2018-10-15 DOI: 10.1145/3277593.3277605

Maria Grammatopoulou, Aris Kanellopoulos, K. Vamvoudakis

引用次数: 1

Using topic models to mine everyday object usage routines through connected IoT sensors 使用主题模型通过连接的物联网传感器挖掘日常对象使用例程

Proceedings of the 8th International Conference on the Internet of Things Pub Date : 2018-07-11 DOI: 10.1145/3277593.3277634

Yanxia Zhang, H. Hung

{"title":"Using topic models to mine everyday object usage routines through connected IoT sensors","authors":"Yanxia Zhang, H. Hung","doi":"10.1145/3277593.3277634","DOIUrl":"https://doi.org/10.1145/3277593.3277634","url":null,"abstract":"With the tremendous progress in sensing and IoT infrastructure, it is foreseeable that IoT systems will soon be available for commercial markets, such as in people's homes. In this paper, we present a deployment study using sensors attached to household objects to capture the resourcefulness of three individuals. The concept of resourcefulness highlights the ability of humans to repurpose objects spontaneously for a different use case than was initially intended. It is a crucial element for human health and wellbeing, which is of great interest for various aspects of HCI and design research. Traditionally, resourcefulness is captured through ethnographic practice. Ethnography can only provide sparse and often short duration observations of human experience, often relying on participants being aware of and remembering behaviours or thoughts they need to report on. Our hypothesis is that resourcefulness can also be captured through continuously monitoring objects being used in everyday life. We developed a system that can record object movement continuously and deployed them in homes of three elderly people for over two weeks. We explored the use of probabilistic topic models to analyze the collected data and identify common patterns.","PeriodicalId":129822,"journal":{"name":"Proceedings of the 8th International Conference on the Internet of Things","volume":"1606 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127449370","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

Proceedings of the 8th International Conference on the Internet of Things 第八届物联网国际会议论文集

Proceedings of the 8th International Conference on the Internet of Things Pub Date : 2016-11-07 DOI: 10.1145/3277593

Stefan Schneegass, A. Schmidt, F. Michahelles, Mareike Kritzler, A. Ilic, Kai Kunze

引用次数: 1