Developing IoT Applications for Future Networks

2017 ◽  
pp. 171-201
Keyword(s):  
Market Potential ◽  
Sensor Data ◽  
Heterogeneous Devices ◽  
Machine Type ◽  
Iot Applications ◽  
Crowd Sensing ◽  
Future Networks ◽  
Machine Type Communication ◽  
Mobile Crowd ◽  
Application Prospects

Applications in the IoT domain need to manage and integrate huge amounts of heterogeneous devices. Usually these devices are treated as external dependencies residing at the edge of the infrastructure mainly transmitting sensed data or reacting to their environment. Recently, these devices will fuel the evolution of the IoT as they feed sensor data to the Internet at a societal scale. Leveraging volunteers and their mobiles as a sensing data collection outlet is known as Mobile Crowd Sensing (MCS) and poses interesting challenges, with particular regard to the management of sensing resource contributors, dealing with their subscription, random and unpredictable join and leave, and node churn. In addition, with the advent of new wireless technologies, it is expected that the use of Machine-Type Communication (MTC) will significantly increase in next generation IoT. MTC has broad application prospects and market potential. In this chapter, we explore new IoT applications for future IoT paradigms.

scholarly journals Pavement Management Utilizing Mobile Crowd Sensing

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Boquan Tian ◽  
Yongbo Yuan ◽  
Hengyu Zhou ◽  
Zhen Yang
Keyword(s):  
Data Collection ◽  
Inertial Sensor ◽  
Pavement Management ◽  
Sensor Data ◽  
Smart Devices ◽  
Smart Device ◽  
Road Transportation ◽  
Mobile Crowd Sensing ◽  
Crowd Sensing ◽  
Mobile Crowd

Pavement management, which is vital in road transportation and maintenance, is facing some troubles, such as high costs of labors and machineries, low detecting efficiency, and low update rate of pavement conditions by means of traditional detection ways. Benefiting from the development of mobile communication, mobile computing, and mobile sensing techniques, the intelligence of mobile crowd sensing (MCS), which mainly relies on ubiquitous mobile smart devices in people’s daily lives, has overcome the above drawbacks to a large extent as one new effective and simple measure for pavement management. As a platform for data collection, processing, and visualization, a common smart device can utilize inertial sensor data, photos, videos, subjective reports, and location information to involve the public in pavement anomalies detection. This paper systematically reviewed the studies in this field from 2008 to 2018 to establish an overall knowledge. Through literature collection and screening, a database of studies was set up for analysis. As a result, the year profile of publications and distribution of research areas indicate that there has been a constant attention from researchers in various disciplines. Meanwhile, the distribution of research topic shows that inertial sensors embedded in smartphones have been the most popular data source. Therefore, the process of pavement anomalies detection based on inertial data was reviewed in detail, including preparatory, data collection, and processing phases of the previous experiments. However, some of the key issues in the experimental phases were investigated by previous studies, while some other challenges were not tackled or noticed. Hence, the challenges in both experiment and implementation stages were discussed to improve the studies and practice. Furthermore, several directions for future research are summarized from the main issues and challenges to offer potential opportunities for more relevant research studies and applications in pavement management.

Code-Division OFDM Joint Communication and Sensing System for 6G Machine-type Communication

2021 ◽  
pp. 1-1
Author(s):  
Xu Chen ◽  
Zhiyong Feng ◽  
Zhiqing Wei ◽  
Ping Zhang ◽  
Xin Yuan
Keyword(s):  
Machine Type ◽  
Sensing System ◽  
Machine Type Communication

ULPT: A User-Centric Location Privacy Trading Framework for Mobile Crowd Sensing

2021 ◽  
pp. 1-1
Author(s):  
Wenqiang Jin ◽  
Mingyan Xiao ◽  
Linke Guo ◽  
Lei Yang ◽  
Ming Li
Keyword(s):  
Location Privacy ◽  
Mobile Crowd Sensing ◽  
Crowd Sensing ◽  
User Centric ◽  
Mobile Crowd

scholarly journals Distributed Group Location Update Algorithm for Massive Machine Type Communication

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7336
Author(s):  
Mincheol Paik ◽  
Haneul Ko
Keyword(s):  
Outage Probability ◽  
Stochastic Game ◽  
Location Update ◽  
Response Dynamics ◽  
Small Energy ◽  
Machine Type ◽  
Best Response ◽  
Machine Type Communication ◽  
Iot Devices ◽  
The Individual

Frequent location updates of individual Internet of Things (IoT) devices can cause several problems (e.g., signaling overhead in networks and energy depletion of IoT devices) in massive machine type communication (mMTC) systems. To alleviate these problems, we design a distributed group location update algorithm (DGLU) in which geographically proximate IoT devices determine whether to conduct the location update in a distributed manner. To maximize the accuracy of the locations of IoT devices while maintaining a sufficiently small energy outage probability, we formulate a constrained stochastic game model. We then introduce a best response dynamics-based algorithm to obtain a multi-policy constrained Nash equilibrium. From the evaluation results, it is demonstrated that DGLU can achieve an accuracy of location information that is comparable with that of the individual location update scheme, with a sufficiently small energy outage probability.

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