SCoTv2: Large Scale Data Acquisition, Processing, and Visualization Platform

Santiago, Ana Rita; Antunes, Mário; Barraca, João Paulo; Gomes, Diogo; Aguiar, Rui L.

doi:10.1109/ficloud.2019.00053

Cited by 3 publications

(6 citation statements)

References 11 publications

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“…Before detailing our SCoT2.0 IoT platform, it is relevant to analyse existing solutions and services. As previously stated, this platform is an evolution over previous SCotv1 [ 4 , 5 ], and as such, most of the background analysis is already presented on them. Nevertheless, this section briefly summarises the key lines described in previous works.…”

Section: State Of the Artmentioning

confidence: 99%

“…Previously, we developed an IoT platform named Smart Cloud of Things (SCoT)v1 [ 3 , 4 , 5 ]. This was developed in close collaboration with Telecom providers, providing a service infrastructure implemented in a telecommunication framework.…”

Section: Introductionmentioning

confidence: 99%

“…As SCoTv1 was used in the deployment of IoT scenarios, it became evident that the European Telecommunications Standards Institute (ETSI) IoT standards were too complex and limited for the realisation of larger scenarios, which became commonplace in the intervening years. This led to several evolutions in our platform [ 5 , 6 ]. The first evolution was replacing the complex ETSI IoT standards with the agile Eclipse IoT.…”

Section: Introductionmentioning

confidence: 99%

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Building an IoT Platform Based on Service Containerisation

Antunes

Santiago

Manso

et al. 2021

Sensors

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IoT platforms have become quite complex from a technical viewpoint, becoming the cornerstone for information sharing, storing, and indexing given the unprecedented scale of smart services being available by massive deployments of a large set of data-enabled devices. These platforms rely on structured formats that exploit standard technologies to deal with the gathered data, thus creating the need for carefully designed customised systems that can handle thousands of heterogeneous data sensors/actuators, multiple processing frameworks, and storage solutions. We present the SCoT2.0 platform, a generic-purpose IoT Platform that can acquire, process, and visualise data using methods adequate for both real-time processing and long-term Machine Learning (ML)-based analysis. Our goal is to develop a large-scale system that can be applied to multiple real-world scenarios and is potentially deployable on private clouds for multiple verticals. Our approach relies on extensive service containerisation, and we present the different design choices, technical challenges, and solutions found while building our own IoT platform. We validate this platform supporting two very distinct IoT projects (750 physical devices), and we analyse scaling issues within the platform components.

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Section: State Of the Artmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Building an IoT Platform Based on Service Containerisation

Antunes

Santiago

Manso

et al. 2021

Sensors

Self Cite

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“…The assistant communicates with them through a control service, also running in the home server. Communication with the remaining appliances/devices relies on SCoT (Smart Cloud of Things) [ 50 ].…”

Section: Smart Home Demonstratormentioning

confidence: 99%

“…For each of the other devices, their information is kept up to date by listening to one or more RabbitMQ queues, using the Advanced Message Queuing Protocol (AMQP). Information is published in the queue(s) by SCoT [ 50 ], which receives it periodically from the corresponding device. In the case of device control, the assistant sends a control request to SCoT, which relays it to the appropriate device.…”

Section: Smart Home Demonstratormentioning

confidence: 99%

An Accessible Smart Home Based on Integrated Multimodal Interaction

Rocha

Ketsmur

Almeida

et al. 2021

Sensors

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Our homes are becoming increasingly sensorized and smarter. However, they are also becoming increasingly complex, making accessing them and their advantages difficult. Assistants have the potential for improving the accessibility of smart homes, by providing everyone with an integrated, natural, and multimodal way of interacting with the home’s ecosystem. To demonstrate this potential and contribute to more environmentally friendly homes, in the scope of the project Smart Green Homes, a home assistant highly integrated with an ICT (Information and communications technology) home infrastructure was developed, deployed in a demonstrator, and evaluated by seventy users. The users’ global impression of our home assistant is in general positive, with 61% of the participants rating it as good or excellent overall and 51% being likely or very likely to recommend it to others. Moreover, most think that the assistant enhances interaction with the smart home’s multiple devices and is easy to use by everyone. These results show that a home assistant providing an integrated view of a smart home, through natural, multimodal, and adaptive interaction, is a suitable solution for enhancing the accessibility of smart homes and thus contributing to a better living ambient for all of their inhabitants.

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