Lessons and experiences of a DIY smart home

Abdallah, Raef; Xu, Lanyu; Shi, Weisong

doi:10.1145/3132479.3132488

Cited by 10 publications

(6 citation statements)

References 12 publications

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“…In addition to indoor activity detection, surveillance systems play an important role in protecting the home security both indoor and outside. Because the video stream occupies a considerable storage space and transmission bandwidth, it is almost impossible to upload every frame recorded from a surveillance system to the cloud for further processing, especially for high resolution videos [79]. EI enables a surveillance device to have certain image processing capabilities, such as object recognition and activity detection, to extract valid information from redundant videos to save unnecessary computing and storage space.…”

Section: Smart Homesmentioning

confidence: 99%

OpenEI: An Open Framework for Edge Intelligence

Zhang

Wang

et al. 2019

2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS)

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100

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1 Abstract-In the last five years, edge computing has attracted tremendous attention from industry and academia due to its promise to reduce latency, save bandwidth, improve availability, and protect data privacy to keep data secure. At the same time, we have witnessed the proliferation of AI algorithms and models which accelerate the successful deployment of intelligence mainly in cloud services. These two trends, combined together, have created a new horizon: Edge Intelligence (EI). The development of EI requires much attention from both the computer systems research community and the AI community to meet these demands.However, existing computing techniques used in the cloud are not applicable to edge computing directly due to the diversity of computing sources and the distribution of data sources. We envision that there missing a framework that can be rapidly deployed on edge and enable edge AI capabilities. To address this challenge, in this paper we first present the definition and a systematic review of EI. Then, we introduce an Open Framework for Edge Intelligence (OpenEI), which is a lightweight software platform to equip edges with intelligent processing and data sharing capability. We analyze four fundamental EI techniques which are used to build OpenEI and identify several open problems based on potential research directions. Finally, four typical application scenarios enabled by OpenEI are presented.

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Section: Smart Homesmentioning

confidence: 99%

OpenEI: An Open Framework for Edge Intelligence

Zhang

Wang

et al. 2019

2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS)

Self Cite

100

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“…One classic example of a smart home task is the aggregation and pre-processing of home video surveillance streams [243]*. Such a case was examined by Abdallah et al [245]* in a prototype system. Their results indicate that the storage of all sensor data in the cloud impacts the available bandwidth for the home significantly, pointing to edge computing as a solution.…”

Section: ) Smart Home/buildingmentioning

confidence: 99%

What the Fog? Edge Computing Revisited: Promises, Applications and Future Challenges

et al. 2019

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Edge computing brings computing and storage resources closer to (mobile) end users and data sources, thus bypassing expensive and slow links to distant cloud computing infrastructures. Often leveraged opportunistically, these heterogeneous resources can be used to offload data and computations, enabling upcoming demanding applications such as augmented reality and autonomous driving. Research in this direction has addressed various challenges, from architectural concerns to runtime optimizations. As of today, however, we lack a widespread availability of edge computing-partly because it remains unclear which of the promised benefits of edge computing are relevant for what types of applications. This article provides a comprehensive snapshot of the current edge computing landscape, with a focus on the application perspective. We outline the characteristics of edge computing and its postulated benefits and drawbacks. To understand the functional composition of applications, we first define common application components that are relevant w.r.t. edge computing. We then present a classification of proposed use cases and analyze them according to their expected benefits from edge computing and which components they use. Furthermore, we illustrate existing products and industry solutions that have recently surfaced and outline future research challenges. INDEX TERMS Edge computing, heterogeneous networks, next generation networking mobile applications, Internet of Things, ubiquitous computing.

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“…Home and business owners rely on such a system to examine their property, people, and events. Police departments reach out to homeowners with surveillance cameras to get assistance in solving crimes more rapidly [1].…”

Section: A Smart Connected Camerasmentioning

confidence: 99%

“…Remote surveillance technologies through the use of home devices, such as smart cameras, is an area that is gaining momentum to ensure home security. Many attribute this to the thriving of the Internet of Things (IoT), low cost of electronic devices such as image sensors, and advancement of image processing [1]. This progression spread the use of camera surveillance systems to privately owned properties.…”

Section: Introductionmentioning

confidence: 99%

“…The IoT is typically described as a combination of technologies that include sensors, actuators, and smart devices with the purpose of connecting different things for increased convenience and productivity. The number of IoT devices is growing rapidly, with recent surveys estimating the number of such devices to exceed 20 billion by 2020 1 . Fuelled by the growth of the IoT, according to a research report by IHS Markit [2], in 2017, 98 million network surveillance cameras and 29 million HD CCTV cameras are expected to be distributed globally.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Investigation of Vulnerabilities in Smart Connected Cameras

Bugeja

Jonsson

Jacobsson

2018

2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)

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The Internet of Things is enabling innovative services promising added convenience and value in various domains such as the smart home. Increasingly, households, office environments and cities, are being fitted with smart camera systems aimed to enhance the security of citizens. At the same time, several systems being deployed suffer from weak security implementations. Recognizing this, and to understand the extent of this situation, in this study we perform a global vulnerability assessment using the Shodan search engine and the Common Vulnerabilities and Exposures database. This is done to detect smart connected cameras exposed on the Internet alongside their sensitive, potentially private, data being broadcasted. Furthermore, we discuss whether the discovered data can be used to compromise the safety and privacy of individuals, and identify some mitigations that can be adopted. The results indicate that a significant number of smart cameras are indeed prone to diverse security and privacy vulnerabilities.

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Lessons and experiences of a DIY smart home

Cited by 10 publications

References 12 publications

OpenEI: An Open Framework for Edge Intelligence

OpenEI: An Open Framework for Edge Intelligence

What the Fog? Edge Computing Revisited: Promises, Applications and Future Challenges

An Investigation of Vulnerabilities in Smart Connected Cameras

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