Data collection model in hybrid network for participatory sensing

Author(s):  
Jeongseok Choi ◽  
Taeyoung Kim ◽  
Jaekwon Kim ◽  
Sunghwan Moon ◽  
Youngshin Han ◽  
...  

Advances in mobile technology make most people have their own mobile devices which contain various sensors such as a smartphone. People produce their own personal data or collect surrounding environment data with their mobile devices at every moment. Recently, a broad spectrum of studies on Participatory Sensing, the concept of extracting new knowledge from a mass of data sent by participants, are conducted. Data collection method is one of the base technologies for Participatory Sensing, so networking and data filtering techniques for collecting a large number of data are the most interested research area. In this paper, we propose a data collection model in hybrid network for participatory sensing. The proposed model classifies data into two types and decides networking form and data filtering method based on the data type to decrease loads on data center and improve transmission speed.

2021 ◽  
Vol 18 ◽  
pp. 42-50
Author(s):  
Darlynton Yartey ◽  
Oladokun Omojola ◽  
Lanre Amodu ◽  
Naomi Ndubueze ◽  
Babatunde Adeyeye ◽  
...  

Marketers have often relied on data to better understand the preferences of the customer base. Whilethe traditional methods were engaged in the retrieval of data, the mobile devices connected to the internetintroduced an influx of data on a real time called big data. Based on this advancement, marketers with thetechnical capacity are able to identify customer needs accurately and identify sway in trends. Although thisstrategy seems beneficial to the marketers, the naïve nature of the customers to the collection and usage ofpersonal online information for mobile marketing remains a crucial poser. Hence, this study through surveysought to identify the awareness level and perception of 700 undergraduates in three higher institutions inLagos, Nigeria. Results show that all the respondents had connected mobile devices, received advertisingmessages on their devices and were active shoppers online. Furthermore, the females were more aware of thecollection and usage of personal data, hence, they embraced the collection based on relevance of advertisingmessages and strict use for mobile marketing. This study therefore recommended marketers’ collection andusage of customers’ personal data to be based on strict use for mobile marketing and assurance of relevance ofadvertising messages.


Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1633 ◽  
Author(s):  
Beom-Su Kim ◽  
Sangdae Kim ◽  
Kyong Hoon Kim ◽  
Tae-Eung Sung ◽  
Babar Shah ◽  
...  

Many applications are able to obtain enriched information by employing a wireless multimedia sensor network (WMSN) in industrial environments, which consists of nodes that are capable of processing multimedia data. However, as many aspects of WMSNs still need to be refined, this remains a potential research area. An efficient application needs the ability to capture and store the latest information about an object or event, which requires real-time multimedia data to be delivered to the sink timely. Motivated to achieve this goal, we developed a new adaptive QoS routing protocol based on the (m,k)-firm model. The proposed model processes captured information by employing a multimedia stream in the (m,k)-firm format. In addition, the model includes a new adaptive real-time protocol and traffic handling scheme to transmit event information by selecting the next hop according to the flow status as well as the requirement of the (m,k)-firm model. Different from the previous approach, two level adjustment in routing protocol and traffic management are able to increase the number of successful packets within the deadline as well as path setup schemes along the previous route is able to reduce the packet loss until a new path is established. Our simulation results demonstrate that the proposed schemes are able to improve the stream dynamic success ratio and network lifetime compared to previous work by meeting the requirement of the (m,k)-firm model regardless of the amount of traffic.


2021 ◽  
Vol 11 (10) ◽  
pp. 4537
Author(s):  
Christian Delgado-von-Eitzen ◽  
Luis Anido-Rifón ◽  
Manuel J. Fernández-Iglesias

Blockchain technologies are awakening in recent years the interest of different actors in various sectors and, among them, the education field, which is studying the application of these technologies to improve information traceability, accountability, and integrity, while guaranteeing its privacy, transparency, robustness, trustworthiness, and authenticity. Different interesting proposals and projects were launched and are currently being developed. Nevertheless, there are still issues not adequately addressed, such as scalability, privacy, and compliance with international regulations such as the General Data Protection Regulation in Europe. This paper analyzes the application of blockchain technologies and related challenges to issue and verify educational data and proposes an innovative solution to tackle them. The proposed model supports the issuance, storage, and verification of different types of academic information, both formal and informal, and complies with applicable regulations, protecting the privacy of users’ personal data. This proposal also addresses the scalability challenges and paves the way for a global academic certification system.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sujen Man Maharjan ◽  
Anubhuti Poudyal ◽  
Alastair van Heerden ◽  
Prabin Byanjankar ◽  
Ada Thapa ◽  
...  

Abstract Background Passive sensor data from mobile devices can shed light on daily activities, social behavior, and maternal-child interactions to improve maternal and child health services including mental healthcare. We assessed feasibility and acceptability of the Sensing Technologies for Maternal Depression Treatment in Low Resource Settings (StandStrong) platform. The StandStrong passive data collection platform was piloted with adolescent and young mothers, including mothers experiencing postpartum depression, in Nepal. Methods Mothers (15–25 years old) with infants (< 12 months old) were recruited in person from vaccination clinics in rural Nepal. They were provided with an Android smartphone and a Bluetooth beacon to collect data in four domains: the mother’s location using the Global Positioning System (GPS), physical activity using the phone’s accelerometer, auditory environment using episodic audio recording on the phone, and mother-infant proximity measured with the Bluetooth beacon attached to the infant’s clothing. Feasibility and acceptability were evaluated based on the amount of passive sensing data collected compared to the total amount that could be collected in a 2-week period. Endline qualitative interviews were conducted to understand mothers’ experiences and perceptions of passive data collection. Results Of the 782 women approached, 320 met eligibility criteria and 38 mothers (11 depressed, 27 non-depressed) were enrolled. 38 mothers (11 depressed, 27 non-depressed) were enrolled. Across all participants, 5,579 of the hour-long data collection windows had at least one audio recording [mean (M) = 57.4% of the total possible hour-long recording windows per participant; median (Mdn) = 62.6%], 5,001 activity readings (M = 50.6%; Mdn = 63.2%), 4,168 proximity readings (M = 41.1%; Mdn = 47.6%), and 3,482 GPS readings (M = 35.4%; Mdn = 39.2%). Feasibility challenges were phone battery charging, data usage exceeding prepaid limits, and burden of carrying mobile phones. Acceptability challenges were privacy concerns and lack of family involvement. Overall, families’ understanding of passive sensing and families’ awareness of potential benefits to mothers and infants were the major modifiable factors increasing acceptability and reducing gaps in data collection. Conclusion Per sensor type, approximately half of the hour-long collection windows had at least one reading. Feasibility challenges for passive sensing on mobile devices can be addressed by providing alternative phone charging options, reverse billing for the app, and replacing mobile phones with smartwatches. Enhancing acceptability will require greater family involvement and improved communication regarding benefits of passive sensing for psychological interventions and other health services. Registration International Registered Report Identifier (IRRID): DERR1-10.2196/14734


2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Kok-Seng Wong ◽  
Myung Ho Kim

The Internet of Things (IoT) is now an emerging global Internet-based information architecture used to facilitate the exchange of goods and services. IoT-related applications are aiming to bring technology to people anytime and anywhere, with any device. However, the use of IoT raises a privacy concern because data will be collected automatically from the network devices and objects which are embedded with IoT technologies. In the current applications, data collector is a dominant player who enforces the secure protocol that cannot be verified by the data owners. In view of this, some of the respondents might refuse to contribute their personal data or submit inaccurate data. In this paper, we study a self-awareness data collection protocol to raise the confidence of the respondents when submitting their personal data to the data collector. Our self-awareness protocol requires each respondent to help others in preserving his privacy. The communication (respondents and data collector) and collaboration (among respondents) in our solution will be performed automatically.


2015 ◽  
Vol 38 ◽  
Author(s):  
Gleb P. Shumyatsky ◽  
Tanja Jovanovic ◽  
Talma Handler

AbstractQuantifying resilience allows for several testable hypotheses, such as that resilience is equal to the number of mental health problems given a known quantity of stressor load. The proposed model lends itself well to prospective studies with data collection pre- and post-adversity; however, prestressor assessments are not always available. Challenges remain for adapting quantifying resilience to animal research, even if the idea of its translation value is significant.


2018 ◽  
Vol 4 (10) ◽  
pp. 116 ◽  
Author(s):  
Robail Yasrab

This research presents the idea of a novel fully-Convolutional Neural Network (CNN)-based model for probabilistic pixel-wise segmentation, titled Encoder-decoder-based CNN for Road-Scene Understanding (ECRU). Lately, scene understanding has become an evolving research area, and semantic segmentation is the most recent method for visual recognition. Among vision-based smart systems, the driving assistance system turns out to be a much preferred research topic. The proposed model is an encoder-decoder that performs pixel-wise class predictions. The encoder network is composed of a VGG-19 layer model, while the decoder network uses 16 upsampling and deconvolution units. The encoder of the network has a very flexible architecture that can be altered and trained for any size and resolution of images. The decoder network upsamples and maps the low-resolution encoder’s features. Consequently, there is a substantial reduction in the trainable parameters, as the network recycles the encoder’s pooling indices for pixel-wise classification and segmentation. The proposed model is intended to offer a simplified CNN model with less overhead and higher performance. The network is trained and tested on the famous road scenes dataset CamVid and offers outstanding outcomes in comparison to similar early approaches like FCN and VGG16 in terms of performance vs. trainable parameters.


2018 ◽  
Vol 9 (2) ◽  
pp. 200-203
Author(s):  
Lydia Febrina Sipahutar

During this time many people were found to achieve the required high learningachievement intellectual intelligence (IQ) is also high. However, EQ good can determine thesuccess of individuals in learning achievement in building a successful career, and can reducethe aggressiveness, especially among teenagers purpose of this study was to determinewhether there is a relationship of emotional intelligence toward student learning achievementProdi DIII Midwifery Curup Semester II and IV. This research was conducted in the ProdiDIII Midwifery Curup from July to August 2016, with the number of respondents, thisresearch is descriptive analytic, data collection using a scale based on the theory of emotionalintelligence Daniel Goleman; to measure student achievement used methods of examinationof documents by the second half saw the value of IP, IV and population II and IV semesterstudent, taken by total population, the data was analyzed by univariate and bivariate. Theresults of the analysis of experimental data showed correlation coefficient of 0.635 with p0.005 (<0.05), the Ha accepted. This means that there is a significant relationship betweenemotional intelligence and academic achievement of students Prodi DIII Midwifery Curup IIand IV semester of 2016. To develop and optimize the emotional intelligence plays a role instudent success both in school and in the surrounding environment, it is recommended to thecampus, especially the lecturer-dosenagar incorporate elements emosioal intelligence inpresenting the material as well as the emotions involved in the learning process


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