Perspectives on M2M protocols

Elgazzar, Mohamed H.

doi:10.1109/intelcis.2015.7397267

Cited by 14 publications

(2 citation statements)

References 9 publications

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“…This component provides support to the messages exchanged during the registration phase and the triggering action of each IoT device. It also plays a central role during the communication between the remote public/private Cloud platforms and the devices (through the BEMW) when they act as actuators and during the internal communications with its specific protocol modules (CoAP, MQTT, LwM2M, ...) [16]. • BodyEdge Manager (BEM): It is used by the BE-GTW when a local data processing can be performed without using external Cloud resources or facilities.…”

Section: B Be-gtw Architecturementioning

confidence: 99%

An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0

Pace

Aloi

Gravina

et al. 2019

IEEE Trans. Ind. Inf.

333

117

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Edge computing paradigm has attracted many interests in the last few years as a valid alternative to the standard Cloud-based approaches to reduce the interaction timing and the huge amount of data coming from IoT devices toward the Internet. In the next future, Edge-based approaches will be essential to support time-dependent applications in the Industry 4.0 context; thus, the paper proposes BodyEdge, a novel architecture well suited for human-centric applications, in the context of the emerging healthcare industry. It consists of a tiny mobile client module and a performing Edge gateway supporting multi-radio and multi-technology communication to collect and locally process data coming from different scenarios; moreover, it also exploits the facilities made available from both private and public Cloud platforms to guarantee a high flexibility, robustness and adaptive service level. The advantages of the designed software platform have been evaluated in terms of reduced transmitted data and processing time through a real implementation on different hardware platforms. The conducted study also highlighted the network conditions (data load and processing delay) in which BodyEdge is a valid and inexpensive solution for healthcare application scenarios.

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Section: B Be-gtw Architecturementioning

confidence: 99%

An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0

Pace

Aloi

Gravina

et al. 2019

IEEE Trans. Ind. Inf.

333

117

View full text Add to dashboard Cite

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“…To address firmware updates and device management, the Open Mobile Alliance (OMA) has standardized OMA Device Management (DM) for mobile devices (e.g., smartphones) [13] and Lightweight Machine-to-Machine (LwM2M) for constrained devices [12]. LwM2M is a lighter version of OMA DM [14] and offers several features for the management, such as monitoring, updating firmware, and the configuration of the devices [6]. In the standardized OMA LwM2M architecture, the device must support CoAP (Constrained Application Protocol) to implement the LwM2M Firmware Update object, but the firmware update itself can be downloaded using other protocols such as HTTP (Hypertext Transfer Protocol) [15].…”

Section: Related Workmentioning

confidence: 99%

Open Sensor Manager for IIoT

Ala-Laurinaho

Autiosalo

Tammi

2020

JSAN

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Data collection in an industrial environment enables several benefits: processes and machinery can be monitored; the performance can be optimized; and the machinery can be proactively maintained. To collect data from machines or production lines, numerous sensors are required, which necessitates a management system. The management of constrained IoT devices such as sensor nodes is extensively studied. However, the previous studies focused only on the remote software updating or configuration of sensor nodes. This paper presents a holistic Open Sensor Manager (OSEMA), which addresses also generating software for different sensor models based on the configuration. In addition, it offers a user-friendly web interface, as well as a REST API (Representational State Transfer Application Programming Interface) for the management. The manager is built with the Django web framework, and sensor nodes rely on ESP32-based microcontrollers. OSEMA enables secure remote software updates of sensor nodes via encryption and hash-based message authentication code. The collected data can be transmitted using the Hypertext Transfer Protocol (HTTP) and Message Queuing Telemetry Transport (MQTT). The use of OSEMA is demonstrated in an industrial domain with applications estimating the usage roughness of an overhead crane and tracking its location. OSEMA enables retrofitting different sensors to existing machinery and processes, allowing additional data collection.

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