Reality mining: sensing complex social systems

Pattern Classification

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The active badge location system

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Pattern Classification

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Using GPS to learn significant locations and predict movement across multiple users

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Place Lab: Device Positioning Using Radio Beacons in the Wild

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Learning and inferring transportation routines

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Implementing a sentient computing system

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ContextPhone: A Prototyping Platform for Context-Aware Mobile Applications

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Social Serendipity: Mobilizing Social Software

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The familiar stranger

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Elimination of the Travel Diary: Experiment to Derive Trip Purpose from Global Positioning System Travel Data

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LeZi-update

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Time series segmentation for context recognition in mobile devices

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The PARCTAB mobile computing system

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Supporting group collaboration with interpersonal awareness devices

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Tracking mobile users in wireless communications networks

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Adaptive On-Device Location Recognition

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Rhythm modeling, visualizations and applications

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Sensing and modeling human networks

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Untitled work

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Activity-based Information Retrieval: Technology in Support of Personal Memory

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Modeling and analysis of the dynamic location registration and paging in microcellular systems

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IntelliBadge™: Towards providing location-aware value-added services at academic conferences

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LifeNet: A Propositional Model of Ordinary Human Activity

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Using Handheld Devices in Synchronous Collaborative Scenarios

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Sensor signal data set for exploring context recognition of mobile devices

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IntelliBadgeTM: Towards Providing Location-Aware Value-Added Services at Academic Conferences

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Using Handheld Devices in Synchronous Collaborative Scenarios

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Parasitic mobility for sensate media

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Handheld and ubiquitous computing : second International Symposium, HUC 2000, Bristol, UK, September 25-27, 2000 : proceedings

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Machine learning: Algorithms, real-world applications and research directions

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Computational social science

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Limits of Predictability in Human Mobility

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Temporal networks

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Just-in-time adaptive interventions (JITAIs) in mobile health: key components and design principles for ongoing health behavior support

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Smart cities of the future

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Inferring friendship network structure by using mobile phone data

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StudentLife: assessing mental health, academic performance and behavioral trends of college students using smartphones

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Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning

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Social signal processing: Survey of an emerging domain

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The IoT for smart sustainable cities of the future: an analytical framework for sensor-based big data applications for environmental sustainability

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Spotting fake reviewer groups in consumer reviews

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Unravelling daily human mobility motifs

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Data Science and Analytics: An Overview from Data-Driven Smart Computing, Decision-Making and Applications Perspective

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Exploiting place features in link prediction on location-based social networks

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Mental health monitoring with multimodal sensing and machine learning: A survey

Garcia-Ceja, E., Riegler, M., Nordgreen, T., Jakobsen, P., Oedegaard, K. J., & Tørresen, J. (2018) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2018.09.003 · Cited by 356 · see citing works

Mind the theoretical gap: interpreting, using, and developing behavioral theory in HCI research

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Mobile Sensing and Support for People With Depression: A Pilot Trial in the Wild

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Do life-logging technologies support memory for the past?: an experimental study using sensecam

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Effectiveness analysis of machine learning classification models for predicting personalized context-aware smartphone usage

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Daily Stress Recognition from Mobile Phone Data, Weather Conditions and Individual Traits

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Mobile Data Science and Intelligent Apps: Concepts, AI-Based Modeling and Research Directions

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Social networks – the future for health care delivery

Griffiths, F., Cave, J., Boardman, F., Ren, J., Pawlikowska, T., Ball, R., Clarke, A., & Cohen, A. (2012) · Social Science & Medicine · doi:10.1016/j.socscimed.2012.08.023 · Cited by 196 · see citing works

BehavDT: A Behavioral Decision Tree Learning to Build User-Centric Context-Aware Predictive Model

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An infectious disease model on empirical networks of human contact: bridging the gap between dynamic network data and contact matrices

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EMMA: an emotion-aware wellbeing chatbot

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A machine learning based robust prediction model for real-life mobile phone data

Sarker, I. H. (2019) · Internet of Things · doi:10.1016/j.iot.2019.01.007 · Cited by 113 · see citing works

Advances in Crowd Analysis for Urban Applications Through Urban Event Detection

Kaiser, M. S., Lwin, K. T., Mahmud, M., Hajializadeh, D., Chaipimonplin, T., Sarhan, A., & Hossain, M. A. (2018) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2017.2771746 · Cited by 98 · see citing works

Context-aware rule learning from smartphone data: survey, challenges and future directions

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Student Perspectives on Digital Phenotyping: The Acceptability of Using Smartphone Data to Assess Mental Health

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ABC-RuleMiner: User behavioral rule-based machine learning method for context-aware intelligent services

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Individualized Time-Series Segmentation for Mining Mobile Phone User Behavior

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RecencyMiner: mining recency-based personalized behavior from contextual smartphone data

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Predicting depressive symptom severity through individuals’ nearby Bluetooth device count data collected by mobile phones: preliminary longitudinal study

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Happiness Recognition from Mobile Phone Data

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Inductive Logic Programming as Abductive Search

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WAKEY: Assisting Parent-child Communication for Better Morning Routines

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Measuring Bus Passenger Load by Monitoring Wi-Fi Transmissions from Mobile Devices

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Sleep, mood and sociability in a healthy population

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Smartphone bluetooth based social sensing

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Evaluating the usefulness of mobile services based on captured usage data from longitudinal field trials

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Optimizing Expectations via Mobile Apps: A New Approach for Examining and Enhancing Placebo Effects

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Preferential Attachment in Online Networks: Measurement and Explanations

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Принципи реалізації Bluetooth 5.2: апаратна реалізація.

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Influence of BlueCore4External on Bluetooth Module

Huang, Z. (2005) · Modern Electronic Technique

Дослідження захищеності Bluetooth-пристроїв на основі смарт-годинників

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PRACTICAL APPLICATION AND PRODUCT DEVELOPMENT ON BLUETOOTH TECHNOLOGY

Jing, H. (2002) · Semiconductor Technology

ІННОВАЦІЙНІ ТЕХНОЛОГІЇ РОЗШИРЕННЯ СПЕКТРУ ДІЇ BLUETOOTH

Сидоренко, О. І. (2022) · Наукові нотатки · doi:10.36910/775.24153966.2022.73.11