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Typical Internet of Things (IoT) and smart home environments are composed of smart devices that are controlled and orchestrated by applications developed and run in the cloud. Correctness is important for these applications, since they control the home's physical security (i.e. door locks) and systems (i.e. HVAC). Unfortunately, many smart home applications and systems exhibit poor security characteristics and insufficient system support. Instead they force application developers to reason about a combination of complicated scenarios-asynchronous events and distributed devices. This paper demonstrates that existing cloud-based smart home platforms provide insufficient support for applications to correctly deal with concurrency and data consistency issues. These weaknesses expose platform vulnerabilities that affect system correctness and security (e.g. a smart lock erroneously unlocked). To address this, we present OKAPI, an application-level API that provides strict atomicity and event ordering. We evaluate our work using the Samsung SmartThings smart home devices, hub, and cloud infrastructure. In addition to identifying shortfalls of cloud-based smart home platforms, we propose design guidelines to make application developers oblivious of smart home platforms' consistency and concurrency intricacies.
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Brain-eNet: Towards an Enabling Technology for BCI-IoT Systems
Brain-Computer Interface (BCI) and Internet of Things (IoT) systems have recently been amalgamated to create BCIoT. Most of the early applications have focused on the healthcare sector, and more recently, in education, virtual reality, smart homes, and smart vehicles, amongst others. While there are many transversal developing stages that can be satisfied by a single system, no common enabling technology or standards exist. These challenges are address in the proposed platform, Brain-eNet. This technology was developed considering the constraints-space defined by BCIoT real-time mobile applications. This is expected to enable the development of BCIoT systems by providing modular hardware and software resources. Two instances of this platform implementation are provided, a motor intent detection for rehabilitation and an emotion recognition system.
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- PAR ID:
- 10463863
- Date Published:
- Journal Name:
- 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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