Cognitive Internet-of-Things solutions enabled by wireless sensor and actuator networks

Tervonen, Jouni; Mikhaylov, Konstantin; Pieskä, Sakari; Jamsa, Joni; Heikkilä, Matti

doi:10.1109/coginfocom.2014.7020426

Cited by 30 publications

(12 citation statements)

References 29 publications

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“…In [13], Tervonen et al states the importance of addressing heterogeneity in a WSN-based IoT application and to leverage on different communication technologies, co-operating among themselves using cognitive infocommunications. They also highlight the importance of energy constraints in IoT nodes and to address it by using energy harvesting techniques.…”

Section: Related Workmentioning

confidence: 99%

An End-To-End LwM2M-Based Communication Architecture for Multimodal NB-IoT/BLE Devices

Basu

Haxhibeqiri

Baert

et al. 2020

Sensors

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The wireless Internet of Things (IoT) landscape is quite diverse. For instance, Low-Power Wide-Area Network (LPWAN) technologies offer low data rate communication over long distance, whereas Wireless Personal Area Network (WPAN) technologies can reach higher data rates, but with a reduced range. For simple IoT applications, communication requirements can be fulfilled by a single technology. However, the requirements of more demanding IoT use cases can vary over time and with the type of data being exchanged. This is pushing the design towards multimodal approaches, where different wireless IoT technologies are combined and the most appropriate one is used as per the need. This paper considers the combination of Narrow Band IoT (NB-IoT) and Bluetooth Low Energy (BLE) as communication options for an IoT device that is running a Lightweight Machine to Machine/Constrained Application Protocol (LwM2M/CoAP) protocol stack. It analyses the challenges incurred by different protocol stack options, such as different transfer modes (IP versus non-IP), the use of Static Context Header Compression (SCHC) techniques, and Datagram Transport Layer Security (DTLS) security modes, and discusses the impact of handover between both communication technologies. A suitable end-to-end architecture for the targeted multimodal communication is presented. Using a prototype implementation of this architecture, an in-depth assessment of handover and its resulting latency is performed.Keywords: multi-modal architecture; handover; narrowband internet of things (NB-IoT); bluetooth low energy (BLE); light-weight machine to machine (LwM2M)

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Section: Related Workmentioning

confidence: 99%

An End-To-End LwM2M-Based Communication Architecture for Multimodal NB-IoT/BLE Devices

Basu

Haxhibeqiri

Baert

et al. 2020

Sensors

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“…Hu et al presented the secure communication between IoT device and destination via wireless energy harvested relay and improved the coverage of an IoT device in CIoT network . Tervonen et al carried out the design and development of wireless sensor network and actuators for IoT solutions and protocols, challenges, solution related to intracognitive and intercognitive is also discussed here …”

Section: Related Workmentioning

confidence: 99%

“…11 Tervonen et al carried out the design and development of wireless sensor network and actuators for IoT solutions and protocols, challenges, solution related to intracognitive and intercognitive is also discussed here. 12…”

Section: Related Workmentioning

confidence: 99%

Analysis of delay‐sensitive performance in cognitive wireless sensor networks

Nazneen

Chowdhury

Sabuj

2019

Internet Technology Letters

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This paper introduces an analytical uplink modeling for cognitive wireless sensor network (CWSN). For such network, we derive the outage probability, throughput, affected area, and delay‐sensitive area spectral efficiency (DASE). In addition, we investigate the DASE maximization problem and also obtain an optimal solution of transmission power and code rate. Finally, numerical results demonstrate that DASE is maximized for optimal transmission power compared with code rate.

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“…They concluded that the inclusion of intelligence and data analysis requires rethinking the architectural choices of IoT solutions. In our earlier work (Tervonen et al, 2014), we also noted the importance of adaptive architecture and discussed some of the CogInfoCom aspects of IoT applications.…”

Section: Figure 1 Model Of Knowledge Gatheringmentioning

confidence: 99%

Survey of business excellence by knowledge gathering for industrial internet-of-things applications

Tervonen

Hautamäki

Heikkilä

et al. 2018

IJMED

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The Internet-of-Things (IoT) can change not only products but also companies' whole business model. The goal of this article is to inform companies about the creation of business intelligence via utilisation of the industrial IoT. This review article assumes that combining business excellence, service design and knowledge gathering via data engineering into cognitive infocommunication (CogInfoCom) opens new possibilities to develop business ideas. These new possibilities are examined through a literature review on deployments of industrial IoT solutions. The survey responds to two research questions: What methods of knowledge gathering and business excellence are used in industrial IoT-based product, service and process innovations? How can knowledge gathering, business Jouni K. Tervonen et al. excellence and CogInfoCom methods be utilised to create added value in industrial IoT solutions? This survey reveals the richness and delicacy of these exploitation opportunities.

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Cognitive Internet-of-Things solutions enabled by wireless sensor and actuator networks

Cited by 30 publications

References 29 publications

An End-To-End LwM2M-Based Communication Architecture for Multimodal NB-IoT/BLE Devices

An End-To-End LwM2M-Based Communication Architecture for Multimodal NB-IoT/BLE Devices

Analysis of delay‐sensitive performance in cognitive wireless sensor networks

Survey of business excellence by knowledge gathering for industrial internet-of-things applications

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