scholarly journals Multilink Internet-of-Things Sensor Communication Based on Bluetooth Low Energy Considering Scalability

Electronics ◽  
2021 ◽  
Vol 10 (19) ◽  
pp. 2335
Author(s):  
Dong-Suk Ryu ◽  
Yeung-Mo Yeon ◽  
Seung-Hee Kim
Keyword(s):  
Internet Of Things ◽  
Low Energy ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Central Processor ◽  
Bluetooth Low Energy ◽  
Switching Algorithm ◽  
Data Errors ◽  
The Internet Of Things ◽  
Central Device

As the growth rate of the internet-of-things (IoT) sensor market is expected to exceed 30%, a technology that can easily collect and processing a large number of various types of sensor data is gradually required. However, conventional multilink IoT sensor communication based on Bluetooth low energy (BLE) enables only the processing of up to 19 peripheral nodes per central device. This study suggested an alternative to increasing the number of IoT sensor nodes while minimizing the addition of a central processor by expanding the number of peripheral nodes that can be processed per central device through a new group-switching algorithm based on Bluetooth low energy (BLE). Furthermore, this involves verifying the relevancy of application to the industry field. This device environment lowered the possibility of data errors and equipment troubles due to communication interference between central processors, which is a critical advantage when applying it to industry. The scalability and various benefits of a group-switching algorithm are expected to help accelerate various services via the application of BLE 5 wireless communication by innovatively improving the constraint of accessing up to 19 nodes per central device in the conventional multilink IoT sensor communication.

Networking solutions for connecting bluetooth low energy enabled machines to the internet of things

IEEE Network ◽  
2014 ◽  
Vol 28 (6) ◽  
pp. 83-90 ◽  
Author(s):  
Johanna Nieminen ◽  
Carles Gomez ◽  
Markus Isomaki ◽  
Teemu Savolainen ◽  
Basavaraj Patil ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Low Energy ◽  
The Internet ◽  
Bluetooth Low Energy ◽  
The Internet Of Things

scholarly journals THE ANALYSIS OF SENSORY PLATFORM FOR USE IN THE INTERNET OF THINGS

2017 ◽  
Vol 7 (3) ◽  
pp. 103-106
Author(s):  
Tomasz Zieliński
Keyword(s):  
Internet Of Things ◽  
Low Energy ◽  
The Internet ◽  
Literature Study ◽  
Bluetooth Low Energy ◽  
Sensor Platforms ◽  
Sensing Platform ◽  
Sensor Platform ◽  
Hub Model ◽  
The Internet Of Things

The main purpose of the work was to analyze sensory platform solutions for use on the Internet of Things. Emphasis was placed on the literature study on Sensor Platforms, Internet of Things, Bluetooth Low Energy Communication Protocol, serial digital and analog interfaces most commonly used in sensory platforms. Analysis of sensory platform solutions was carried out in terms of their functionality and efficiency. The SensorTag CC2650 sensing platform by Texas Instruments, turned out to be the best and has been used to build the hub model. The hub model was based on hardware and software implementation, which resulted in the expansion of the sensor platform with 6 additional analog inputs and a Bluetooth Low Energy data transmission profile. Testing the correctness of the software produced in the laboratory environment has made it possible to determine the correct functioning of the concentrator model.

RFID, NFC, Beacons, and the Infrastructures of Logistical Locative Media

2020 ◽  
pp. 474-486
Author(s):  
Jordan Frith
Keyword(s):  
Internet Of Things ◽  
Radio Frequency Identification ◽  
Near Field ◽  
Low Energy ◽  
Near Field Communication ◽  
Rfid Tags ◽  
Bluetooth Low Energy ◽  
Locative Media ◽  
Frequency Identification ◽  
Machine Readable

The phrase the Internet of things was originally coined in a 1999 presentation about attaching radio frequency identification (RFID) tags to individual objects. These tags would make the objects machine-readable, uniquely identifiable, and, most importantly, wirelessly communicative with infrastructure. This chapter evaluates RFID as a piece of mobile communicative infrastructure, and it examines two emerging forms: near-field communication (NFC) and Bluetooth low-energy beacons. The chapter shows how NFC and Bluetooth low-energy beacons may soon move some types of RFID to smartphones, in this way evolving the use of RFID in payment and transportation and enabling new practices of post-purchasing behaviors.

scholarly journals Implementation of Oxygen Saturation Sensor Data Acquisition Based on Bluetooth Low Energy Protocol

2021 ◽  
Author(s):  
Muhammad Fahmi Ali Fikri ◽  
Dany Primanita Kartikasari ◽  
Adhitya Bhawiyuga
Keyword(s):  
Data Acquisition ◽  
Data Center ◽  
Low Energy ◽  
Sensor Data ◽  
Data Delivery ◽  
Bluetooth Low Energy ◽  
Data Redundancy ◽  
Iot Devices ◽  
Store And Forward ◽  
Sensor Data Acquisition

Sensor data acquisition is used to obtain sensor data from IoT devices that already provide the required sensor data. To acquire sensor data, we can use Bluetooth Low Energy (BLE) protocol. This data acquisition aims to process further data which will later be sent to the server. Bluetooth Low Energy (BLE) has an architecture consisting of sensors, gateways, and data centers, but with this architecture, there are several weaknesses, namely the failure when sending data to the data center due to not being connected to internet network and data redundancy at the time of data delivery is done. The proposed solution to solve this problem is to create a system that can acquire sensor data using the Bluetooth Low Energy (BLE) protocol with use a store and forward mechanism and checking data redundancy. The proposed system will be implemented using sensors from IoT devices, the gateway used is Android devices, and using the Bluetooth Low Energy protocol to acquire data from sensors. Then the data will be sent to the cloud or server. The results of the test give the results of the system being successfully implemented and IoT devices can be connected to the gateway with a maximum distance of 10 meters. Then when the system stores, for every minute there is an increase in data of 4 kb. Then there is no data redundancy in the system.

scholarly journals An Improved Unsupervised Single-Channel Speech Separation Algorithm for Processing Speech Sensor Signals

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Dazhi Jiang ◽  
Zhihui He ◽  
Yingqing Lin ◽  
Yifei Chen ◽  
Linyan Xu
Keyword(s):  
Internet Of Things ◽  
Speech Signal ◽  
Single Channel ◽  
Low Noise ◽  
Sensor Data ◽  
The Internet ◽  
Speech Separation ◽  
Adaptive Wavelet ◽  
Enhancement Technique ◽  
The Internet Of Things

As network supporting devices and sensors in the Internet of Things are leaping forward, countless real-world data will be generated for human intelligent applications. Speech sensor networks, an important part of the Internet of Things, have numerous application needs. Indeed, the sensor data can further help intelligent applications to provide higher quality services, whereas this data may involve considerable noise data. Accordingly, speech signal processing method should be urgently implemented to acquire low-noise and effective speech data. Blind source separation and enhancement technique refer to one of the representative methods. However, in the unsupervised complex environment, in the only presence of a single-channel signal, many technical challenges are imposed on achieving single-channel and multiperson mixed speech separation. For this reason, this study develops an unsupervised speech separation method CNMF+JADE, i.e., a hybrid method combined with Convolutional Non-Negative Matrix Factorization and Joint Approximative Diagonalization of Eigenmatrix. Moreover, an adaptive wavelet transform-based speech enhancement technique is proposed, capable of adaptively and effectively enhancing the separated speech signal. The proposed method is aimed at yielding a general and efficient speech processing algorithm for the data acquired by speech sensors. As revealed from the experimental results, in the TIMIT speech sources, the proposed method can effectively extract the target speaker from the mixed speech with a tiny training sample. The algorithm is highly general and robust, capable of technically supporting the processing of speech signal acquired by most speech sensors.

Bluetooth Low-Energy-Based Applications

2018 ◽  
pp. 95-112
Author(s):  
Smita Sanjay Ambarkar ◽  
Rakhi Dattatraya Akhare
Keyword(s):  
Indoor Localization ◽  
Low Energy ◽  
Smart Devices ◽  
The Internet ◽  
Bluetooth Low Energy ◽  
Iot Applications ◽  
Proximity Detection ◽  
Battery Power ◽  
Commercial Market ◽  
The Internet Of Things

This chapter focuses on the comprehensive contents of various applications and principles related to Bluetooth low energy (BLE). The internet of things (IoT) applications like indoor localization, proximity detection problem by using Bluetooth low energy, and enhancing the sales in the commercial market by using BLE have the same database requirement and common implementation idea. The real-world applications are complex and require intensive computation. These computations should take less time, cost, and battery power. The chapter mainly focuses on the usage of BLE beacons for indoor localization. The motive behind the study of BLE devices is that it is supported by mobile smart devices that augment its application exponentially.

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