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Ubiquitous human perception for real-time gender estimation
2013
2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)
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This system combines ubiquitous smart sensing, methods of multi-modal human perception and existing human recognition algorithms from the field of biometrics to collectively work towards a real-time, robust ...
This paper presents a robotic system that exploits the advantages of ubiquitous perception in order to gather knowledge from multiple sensors and various modalities. ...
Acknowledgement This work has been supported by the Irish Research Council "Embark Initiative", in conjunction with funding from the EU FP7 RUBICON project (contract n. 269914), and Science Foundation ...
doi:10.1109/urai.2013.6677485
dblp:conf/urai/SandygulovaSADO13
fatcat:zzf2wg3iejg5tnsmkfmyd72w5i
Horizontal Review on Video Surveillance for Smart Cities: Edge Devices, Applications, Datasets, and Future Trends
2021
Sensors
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The automation strategy of today's smart cities relies on large IoT (internet of Things) systems that collect big data analytics to gain insights. ...
In this paper, we discuss the latest datasets used, the algorithms used, and the recent advances in embedded systems to form edge vision computing are introduced. ...
The end-users simply use multiple applications once the data are stored on the cloud, such as people counting, crowd estimation, action recognition, age and gender estimation, vehicle estimation and vehicle ...
doi:10.3390/s21093222
pmid:34066509
fatcat:27lploodmvdl3k36x4jzw2acly
Stabilization of Magnified Videos on a Mobile Device for Visually Impaired
2013
2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops
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As digital zoom normally cannot provide sufficient magnification for distant objects, optical telescopic devices attached to the smart phone cameras can be used to increase magnification power. ...
Many apps have been developed to turn a smart phone into a handy video magnifier using digital zoom. ...
Video stabilization particularly helped the visually impaired subjects improve the letter recognition performance as seen from the data. ...
doi:10.1109/cvprw.2013.15
dblp:conf/cvpr/LiPL13
fatcat:i4qeo26umrat7npc4lynkv34ou
Use of the Smart Store for Persuasive Marketing and Immersive Customer Experiences: A Case Study of Korean Apparel Enterprise
2017
Mobile Information Systems
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Furthermore, we present a case study of a business that applies the smart store concept to its fashion retail shops in Korea. ...
This paper aims to summarize discussions related to smart stores and their possible applications in a real business environment. ...
Smart pads and wearable devices provided to employees in stores are used to provide real time trigger to customers by gathering information from smart CCTV, smart hangers, and smart displays and processing ...
doi:10.1155/2017/4738340
fatcat:cx22si3kevgonet4dcif34npcu
Special issue on smart cameras for real-time image and video processing
2020
Journal of Real-Time Image Processing
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, multiple object tracking, face attribute recognition, human detection, image retrieval, and energy-efficient design of smart cameras. ...
a wealth of other smart devices, and of course the Internet. ...
a wealth of other smart devices, and of course the Internet. ...
doi:10.1007/s11554-020-01006-6
fatcat:d3g5hvg5q5hzzfqqj3zbpb4tre
Sensors of Smart Devices in the Internet of Everything (IoE) Era: Big Opportunities and Massive Doubts
2019
Journal of Sensors
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In this work, we attempt to review the process of inferring meaningful data from smart devices' sensors, especially, smartphones. ...
Smart device industry allows developers and designers to embed different sensors, processors, and memories in small-size electronic devices. ...
Motion Sensors. Three main sensors are embedded in modern smart devices for motion detection: accelerometer, gyroscope, and magnetometer. ...
doi:10.1155/2019/6514520
fatcat:lxlva7xfbra7flwt6jby7dc5xy
Classification Algorithms In Human Activity Recognition Using Smartphones
2012
Zenodo
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Recognizing human activity has garnered a lot of interest and has raised significant researches- concerns in identifying contextual information useful to human activity recognition. ...
In this paper, we will discuss the classification algorithms used in smartphone-based human activity. ...
Human activity recognition in smart homes mainly employs contexts' identification and recognition from multimodal features using multiple types of sensors. ...
doi:10.5281/zenodo.1071040
fatcat:oxawccjwijh3zfienzluqzj7ti
HANDY: A Benchmark Dataset for Context-Awareness via Wrist-Worn Motion Sensors
2018
Data
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Here, we offer a solution to the problem with a set of multiple motion sensors worn on the wrist. ...
Second, we present an evaluation of recent computational methods for two relevant tasks: activity recognition and person identification from hand movements. ...
This wearable device mitigated a smart watch that potentially embedded similar motion sensors. ...
doi:10.3390/data3030024
fatcat:3dk4htrvjfdf3ejqf2jt7yfsba
Intelligent Dumbbell Based on Multiple Sensors
2020
Sensors and materials
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However, traditional fitness equipment can be boring and inflexible in its use and does not enable the recording of fitness data, making it difficult for people to monitor fitness data and manage their ...
As small fitness equipment, dumbbells are suitable for people of different ages, genders, and physical fitness levels. ...
(2) n the recognition of wearable sensor motion status, motion status data are collected by attaching wearable sensor devices on people, including acceleration sensors, gyroscopes, and heart rate monitoring ...
doi:10.18494/sam.2020.2779
fatcat:e2vac43zdjhzjki5qncnoztrei
Analysis of Smart Home Technology Acceptance and Preference for Elderly in Dubai, UAE
2021
Designs
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As a methodology, a survey and interview were conducted for 110 people in their 40s and 60s and a total of 105 valid survey responses were collected and used as data for frequency, mean, cross-analysis ...
In the case of sensors, elderly preferred the switch at the entrance (36.2%), and motion detecting sensors (42.9%), video cameras (56.2%), and voice recognition (50.5%) sensors in the living room. ...
A total of 105 questionnaires were collected and used as data, and frequency, mean, cross-analysis, independent sample t-test, one-way variance analysis, and multiple regression analysis were performed ...
doi:10.3390/designs5040070
fatcat:f4jrvwrjy5a5pkht5owecbh5py
A Review of the Recent Developments in Integrating Machine Learning Models with Sensor Devices in the Smart Buildings Sector with a View to Attaining Enhanced Sensing, Energy Efficiency, and Optimal Building Management
2019
Energies
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Lately, many scientists have focused their research on subjects like smart buildings, sensor devices, virtual sensing, buildings management, Internet of Things (IoT), artificial intelligence in the smart ...
Our approach provides a useful up-to-date overview for researchers from different fields, which can be helpful when submitting project proposals or when studying complex topics such those reviewed in this ...
The performance metrics chosen by the authors of the papers focusing on Deep Learning techniques integrated with sensor devices in smart buildings included Confusion Matrices and F1 Accuracy [18] ; Overall ...
doi:10.3390/en12244745
fatcat:eix222pupjcmddolute2qh4wia
Towards a smart retail environment
2015
Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers - UbiComp '15
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, smart watches, touch screens, etc.), offering new interaction methods to virtually present to users personalized products information. ...
Over the last decades, the advancements in digital technologies pervasiveness increasingly transformed regular physical spaces in smart ambients, where humans and objects are seamlessly hyper-connected ...
Acknowledgements This work is partially funded by the EC Commission through EIT Digital "HII Street Smart Retail" Activity and by Telecom Italia S.p.A., Open Innovation Department, Joint Open Lab S-Cube ...
doi:10.1145/2800835.2807955
dblp:conf/huc/RienzoGCFV15
fatcat:jr2cm4ujh5a2bocymqntdkdwbm
Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data
2015
Sensors
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For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. ...
To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. ...
With data from the PIR motion sensors, periods without any activity in the flat were detected. ...
doi:10.3390/s150511725
pmid:26007727
pmcid:PMC4481906
fatcat:ez6w2vy2xvbvjcmdxy3qiyr3a4
A New Intelligent Approach for Deaf/Dumb People based on Deep Learning
2022
Computers Materials & Continua
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The data obtained from the gloves was processed using deep-learning-based approaches and classified multi-mode commands that allow dumb people to speak with regular people via their smart phone. ...
People who are deaf or have difficulty speaking use sign language, which consists of hand gestures with particular motions that symbolize the "language" they are communicating. ...
[19] proposed a real-time gesture recognition system that classifies 11 motions using a data glove, and the recognition result was 100 percent accurate. ...
doi:10.32604/cmc.2022.026309
fatcat:nodx3ljlmjgklhqtu2ftdoal3a
Paper titles
2020
2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)
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Signals from A Portable ECG Acquisition Device
Image Retrieval with Data Augmentation of Sentence Labels Based on ParaphrasingImage-based Skin Temperature and Pulse Rate Measuring System Image-Enhancement-Based ...
Environment and Location Data Indoor Positioning Method for Smart Mobile Device Based on Fuzzy Wi-Fi Fingerprint Influence of Radio Waves Generated by XBee Module on GPS Positioning Performance Influence ...
doi:10.1109/icce-taiwan49838.2020.9258179
fatcat:2eheaztzhncixhbvp7nrbzml4m
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