Bluetooth 5.0 throughput comparison for internet of thing usability a survey

Yaakop, Muhyi; Malik, Izwan Arief Abd; Suboh, Mohd Zubir; Ramli, Aizat Faiz; Abu, Mohd Salleh

doi:10.1109/ice2t.2017.8215995

Cited by 23 publications

(8 citation statements)

References 8 publications

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“…Although during the meantime the Bluetooth v5.0 specifications were made available for the market, test modules were not available until recently. Some aspects regarding Bluetooth v5 were tested in [ 20 ], such as throughput against distance or influence of obstacles, or in [ 21 ] for RSSI against distance. However, it must be mentioned that the tests performed revealed only static behaviour (but not in Wi-Fi interference conditions), and future assessments have to be performed to evaluate the improvements of Bluetooth v5 against older versions in sensor networks, using similar conditions to the ones defined in this paper.…”

Section: Assessment Tests Performed and Resultsmentioning

confidence: 99%

Use of Energy Efficient Sensor Networks to Enhance Dynamic Data Gathering Systems: A Comparative Study between Bluetooth and ZigBee

Gheorghiu

Iordache

2018

Sensors

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As road traffic conditions worsen due to the constantly increasing number of cars, traffic management systems are struggling to provide a suitable environment, by gathering all the relevant information from the road network. However, in most cases these are obtained via traffic detectors placed near road junctions, thus providing no information on the conditions in between. A large-scale sensor network using detectors on the majority of vehicles would certainly be capable of providing useful data, but has two major impediments: the equipment installed on the vehicles should be cheap enough (assuming the willingness of private car owners to be a part of the network) and be capable of transferring the required amount of data in due time, as the vehicle passes by the road side unit that acts as interface with the traffic management system. These restrictions reduce the number of technologies that can be used. In this article a series of comprehensive tests have been performed to evaluate the Bluetooth and ZigBee protocols for this purpose from many points of view: handshake time, static and dynamic data transfer (in laboratory conditions and in real traffic conditions). An assessment of the environmental conditions (during tests and probable to be encountered in real conditions) was also provided.

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Section: Assessment Tests Performed and Resultsmentioning

confidence: 99%

Use of Energy Efficient Sensor Networks to Enhance Dynamic Data Gathering Systems: A Comparative Study between Bluetooth and ZigBee

Gheorghiu

Iordache

2018

Sensors

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“…Newest standards such as 802.11ac advertise a maximum theoretical speed of to 1300 Mbps [ 65 ], with a maximum theoretical range of about 90 m outdoors, and 45 m indoors. Bluetooth 3.0, however, offers a maximum speed of 24 Mbps and a maximum theoretical range of 100 m. Starting from Bluetooth 4.0, a new standard was introduced as Bluetooth Low Energy (BLE), and was further improved in version 5.0, doubling its data rate [ 66 ]. The main goal of BLE is to reduce energy consumption in order to extend battery life of smartphones and wearables.…”

Section: Real-time Centralized Activity Recognitionmentioning

confidence: 99%

From Offline to Real-Time Distributed Activity Recognition in Wireless Sensor Networks for Healthcare: A Review

Baghezza

Bouchard

Bouzouane

et al. 2021

Sensors

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This review presents the state of the art and a global overview of research challenges of real-time distributed activity recognition in the field of healthcare. Offline activity recognition is discussed as a starting point to establish the useful concepts of the field, such as sensor types, activity labeling and feature extraction, outlier detection, and machine learning. New challenges and obstacles brought on by real-time centralized activity recognition such as communication, real-time activity labeling, cloud and local approaches, and real-time machine learning in a streaming context are then discussed. Finally, real-time distributed activity recognition is covered through existing implementations in the scientific literature, and six main angles of optimization are defined: Processing, memory, communication, energy, time, and accuracy. This survey is addressed to any reader interested in the development of distributed artificial intelligence as well activity recognition, regardless of their level of expertise.

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“…Also, it prevents the delay of the transmission. In related papers [8,9], it controls the BLE network congestion by the controls the throughput. The wireless network configuration may vary depending on the degree of radio congestion in the real industrial field.…”

Section: Related Reviewmentioning

confidence: 99%

A Study of BLE Mesh Network Scheduling Algorithm Using A Smartplug

et.al¹

2021

TURCOMAT

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This paper proposes a BLE Mesh network scheduling algorithm using SmartPlug. And proposes random-backoff, a very simple method for collision avoidance. The low-energy scheduling algorithm of SmartPlug and BLE node is proposed. SmartPlug periodically broadcasts its own information to inform the surrounding BLE nodes and SmartPlug. A node for data communication with SmartPlug is decided for efficiency. The BLE node periodically transmits data and switches to sleep mode after data transmission. In this paper, propose a very simple method, random-backoff, to reduce collisions when transmitting data in a BLE node. In the simulation of results shows when the data size is 1 ~ 31 bytes and 32 ~ 255 bytes, and random-backoff is effective when 1~31 bytes length. In the case of 32 to 255 bytes, random-backoff is not effective, so additional research is needed. And the simulation conducts under the same condition, but it shows that the data length and the number of transmission attempts has an effect. The simulation results show the transmission success ratio is similar regardless of the data length when random-backoff is not applied. It also shows the number of transmission attempts has an effect. Also, this simulation shows the results that as the number of nodes increases, the wireless environment becomes congested, and the transmission success ratio decreases. As a result of the simulation, random-backoff for collision avoidance is effective in transmitting data of 1 to 31 bytes better than 32 to 255 bytes in the data length.

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Bluetooth 5.0 throughput comparison for internet of thing usability a survey

Cited by 23 publications

References 8 publications

Use of Energy Efficient Sensor Networks to Enhance Dynamic Data Gathering Systems: A Comparative Study between Bluetooth and ZigBee

Use of Energy Efficient Sensor Networks to Enhance Dynamic Data Gathering Systems: A Comparative Study between Bluetooth and ZigBee

From Offline to Real-Time Distributed Activity Recognition in Wireless Sensor Networks for Healthcare: A Review

A Study of BLE Mesh Network Scheduling Algorithm Using A Smartplug

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