scholarly journals Symbiotic Sensing for Energy-Intensive Tasks in Large-Scale Mobile Sensing Applications

Sensors ◽  
2017 ◽  
Vol 17 (12) ◽  
pp. 2763 ◽  
Author(s):  
Duc Le ◽  
Thuong Nguyen ◽  
Hans Scholten ◽  
Paul Havinga
Keyword(s):  
Large Scale ◽  
Mobile Sensing ◽  
Sensing Applications

scholarly journals Emergent Technologies in Big Data Sensing: A Survey

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Ting Zhu ◽  
Sheng Xiao ◽  
Qingquan Zhang ◽  
Yu Gu ◽  
Ping Yi ◽  
...  
Keyword(s):  
Big Data ◽  
Large Scale ◽  
Data Science ◽  
Mobile Sensing ◽  
Emergent Technologies ◽  
Sensing Applications ◽  
Crowd Sensing ◽  
Multiple Data ◽  
Challenges And Opportunities ◽  
Research Architecture

When the number of data generating sensors increases and the amount of sensing data grows to a scale that traditional methods cannot handle, big data methods are needed for sensing applications. However, big data is a fuzzy data science concept and there is no existing research architecture for it nor a generic application structure in the field of sensing. In this survey, we explore many scattered results that have been achieved by combining big data techniques with sensing and present our vision of big data in sensing. Firstly, we outline the application categories to generally summarize existing research achievements. Then we discuss the techniques proposed in these studies to demonstrate challenges and opportunities in this field. Finally, we present research trends and list some directions of big data in future sensing. Overall, mobile sensing and its related studies are hot topics, but other large-scale sensing researches are flourishing too. Although there are no “big data” techniques acting as research platforms or infrastructures to support various applications, multiple data science technologies, such as data mining, crowd sensing, and cloud computing, serve as foundations and bases of big data in the world of sensing.

scholarly journals PPDC: A Privacy-Preserving Distinct Counting Scheme for Mobile Sensing

2019 ◽  
Vol 9 (18) ◽  
pp. 3695
Author(s):  
Xiaochen Yang ◽  
Ming Xu ◽  
Shaojing Fu ◽  
Yuchuan Luo
Keyword(s):  
Large Scale ◽  
Homomorphic Encryption ◽  
Original Data ◽  
Critical Issue ◽  
Negative Influence ◽  
Privacy Preserving ◽  
Mobile Sensing ◽  
Data Sets ◽  
Counting Problem ◽  
Sensing Applications

Mobile sensing mines group information through sensing and aggregating users’ data. Among major mobile sensing applications, the distinct counting problem aiming to find the number of distinct elements in a data stream with repeated elements, is extremely important for avoiding waste of resources. Besides, the privacy protection of users is also a critical issue for aggregation security. However, it is a challenge to meet these two requirements simultaneously since normal privacy-preserving methods would have negative influence on the accuracy and efficiency of distinct counting. In this paper, we propose a Privacy-Preserving Distinct Counting scheme (PPDC) for mobile sensing. Through integrating the basic idea of homomorphic encryption into Flajolet-Martin (FM) sketch, PPDC allows an aggregator to conduct distinct counting over large-scale datasets without disrupting privacy of users. Moreover, PPDC supports various forms of sensing data, including camera images, location data, etc. PPDC expands each bit of the hashing values of users’ original data, FM sketch is thus enhanced for encryption to protect users’ privacy. We prove the security of PPDC under known-plaintext model. The theoretic and experimental results show that PPDC achieves high counting accuracy and practical efficiency with scalability over large-scale data sets.

Heterogeneous wireless connectivity for fixed and mobile sensing applications in industrial environments

ETFA2011 ◽  
2011 ◽  
Author(s):  
Jose Antonio Palazon ◽  
Miguel Sepulcre ◽  
Javier Gozalvez ◽  
Jaime Orozco ◽  
Oscar Lopez
Keyword(s):  
Mobile Sensing ◽  
Sensing Applications ◽  
Industrial Environments ◽  
Wireless Connectivity

Fabrication of large area nanogap electrodes for sensing applications

2013 ◽  
Vol 1530 ◽  
Author(s):  
A. Bendavid ◽  
L. Wieczorek ◽  
R. Chai ◽  
J. S. Cooper ◽  
B. Raguse
Keyword(s):  
Large Scale ◽  
Focused Ion Beam ◽  
Ion Beam ◽  
Beam Current ◽  
Fabrication Method ◽  
Large Area ◽  
Sensor Applications ◽  
Sensing Applications ◽  
Lift Off ◽  
Nanogap Electrodes

ABSTRACTA large area nanogap electrode fabrication method combinig conventional lithography patterning with the of focused ion beam (FIB) is presented. Lithography and a lift-off process were used to pattern 50 nm thick platinum pads having an area of 300 μm × 300 μm. A range of 30-300 nm wide nanogaps (length from 300 μm to 10 mm ) were then etched using an FIB of Ga+ at an acceleration voltage of 30 kV at various beam currents. An investigation of Ga+ beam current ranging between 1-50 pA was undertaken to optimise the process for the current fabrication method. In this study, we used Monte Carlo simulation to calculate the damage depth in various materials by the Ga+. Calculation of the recoil cascades of the substrate atoms are also presented. The nanogap electrodes fabricated in this study were found to have empty gap resistances exceeding several hundred MΩ. A comparison of the gap length versus electrical resistance on glass substrates is presented. The results thus outline some important issues in low-conductance measurements. The proposed nanogap fabrication method can be extended to various sensor applications, such as chemical sensing, that employ the nanogap platform. This method may be used as a prototype technique for large-scale fabrication due to its simple, fast and reliable features.

Efficient 3G/4G Budget Utilization in Mobile Sensing Applications

2017 ◽  
Vol 16 (6) ◽  
pp. 1601-1614 ◽  
Author(s):  
Chao Xu ◽  
Shaohan Hu ◽  
Wei Zheng ◽  
Tarek F. Abdelzaher ◽  
Pan Hui ◽  
...  
Keyword(s):  
Mobile Sensing ◽  
Sensing Applications

scholarly journals Mobile sensing for behavioral research: A component-based approach for rapid deployment of sensing campaigns

2019 ◽  
Vol 15 (9) ◽  
pp. 155014771987418 ◽  
Author(s):  
Ivan R Felix ◽  
Luis A Castro ◽  
Luis-Felipe Rodriguez ◽  
Oresti Banos
Keyword(s):  
Mobile Phones ◽  
Mobile Sensing ◽  
Timely Manner ◽  
New Approach ◽  
Reusable Components ◽  
Sensing Applications ◽  
Effectiveness And Efficiency ◽  
Multiple Sensing ◽  
Definition Of ◽  
Rapid Deployment

Collecting experimental data from multiple sensing devices has just recently become quite popular in behavioral and social sciences. Among existing devices, mobile phones stand out as they allow researchers to collect data from individuals in an unbiased, precise, unobtrusive, and timely manner. Current mobile sensing applications are typically developed from scratch, provide no reusable components, and frequently do not take advantage of the devices’ processing capabilities. In light of such limitations, this work presents a novel tool that leverages mobile phones not only to collect data via their sensors but also to process them on the device as soon as they are gathered. The tool provides researchers with easy-to-use services that allow them to configure the required processing routines on the mobile phones. This work proposes a new approach for rapid deployment of sensing campaigns targeted at scientists with basic technical knowledge and requiring low effort. We performed an evaluation aimed at determining whether there is a significant improvement in terms of user effectiveness and efficiency in the definition of new components. The results suggest that the proposed tool speeds up the time and reduces the effort taken for setting up and deploying a sensing campaign.

Sign in / Sign up

Export Citation Format

Share Document