QACM: Quality Aware Crowd Sensing in Mobile Computing

Author:

Thippeswamy B. M.1,Ghouse Mohamed2,Ahmed Jafarabad Shanawaz2,Khan Mohammed Murtuza Ahamed3,Adere Ketema1ORCID,B. M. Prabhu Prasad4,B. N. Pavan Kumar5ORCID

Affiliation:

1. Department of Computer Science and Engineering, SoEEC, Adama Science and Technology University, Adama 274509, Ethiopia

2. Department of Computer Science, College of Computer Science King Khalid University, Abha 62529, Saudi Arabia

3. School of Computing, Universiti Teknologi, Johor Bahru 81310, Malaysia

4. Department of Computer Science, Indian Institute of Information Technology, Dharwad 580009, Karnataka, India

5. Department of Computer Science, Indian Institute of Information Technology, Sri City 517646, Andhra Pradesh, India

Abstract

Mobile computing is one of the significant opportunities that can be used for various practical applications in numerous fields in real life. Due to inherent characteristics of ubiquitous computing, devices can gather numerous types of data that led to innovative applications in many fields with a unique emerging prototype known as Crowd sensing. Here, the involvement of people is one of the important features and their mobility provides an exclusive opportunity to collect and transmit the data over a substantial geographical area. Thus, we put forward novel idea about Quality of Information (QOI) with unique parameters with opportunistic uniqueness of people’s mobility in terms of sensing and transmission. Additionally, we propose some of the viable improved ideas about the competent opportunistic data collection through efficient techniques. This work also considered some of the open issues mentioned by previous related works.

Publisher

MDPI AG

Subject

Artificial Intelligence,Applied Mathematics,Industrial and Manufacturing Engineering,Human-Computer Interaction,Information Systems,Control and Systems Engineering

Reference25 articles.

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3. Nava Auza, J.M., Boisson de Marca, J.R., and Lima Siqueira, G. (2019). Design of Local Information incentive Mechanism for Mobile Crowd Sensing. Sensors, 19.

4. Stojanovic, D., Predic, B., and Stojanovic, N. (2016). Europian Handbook of Crowd Sensed Geographic Information, Ubiquity Press Ltd.

5. iLoCuS :Incentivising Vehicle Mobility to Optimize Sensing Distribution in Crowd Sensing;Xu;IEEE Trans. Mob. Comput.,2018

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