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Adabev: Automatic Detection Of Abnormal Behavior In Video-Surveillance
2012
Zenodo
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We present in this paper ADABeV, an intelligent video-surveillance framework for event recognition in crowded scene to detect the abnormal human behaviour. ...
guarantees the high efficiency in the security protection, and save a lot of human and material resources. ...
It aims at detecting the abnormal human behavior, automatically and in real time. ...
doi:10.5281/zenodo.1057171
fatcat:aa2ukdfzujawdpn73rrqwdljpm
Recognizing Context-Aware Human Sociability Patterns Using Pervasive Monitoring for Supporting Mental Health Professionals
2020
Sensors
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As an alternative, we present a solution to detect context-aware sociability patterns and behavioral changes based on social situations inferred from ubiquitous device data. ...
The proposed solution also can detect abnormal behavior and routine changes. ...
Section 3 presents the proposed solution to detect context-aware sociability patterns and changes in social behavior. ...
doi:10.3390/s21010086
pmid:33375630
fatcat:ruyavlolwfbg7aoslunazpseou
Adaptive monitoring system for e-health smart homes
2018
Pervasive and Mobile Computing
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We propose a new context-aware e-health monitoring system targeted at the elderly and isolated persons living alone. ...
It is then able to detect risky behavioral changes by using our novel forecasting approach based on the extension of the Grey model GM(1, 1). ...
Future work includes extending the number of actions considered in our scenario generation in order to refine our knowledge of a person's behavior. ...
doi:10.1016/j.pmcj.2017.11.001
fatcat:2onalchyizcclgnarqej5xlf6y
Modeling Eating Disorders of Cognitive Impaired People
[chapter]
2012
Lecture Notes in Electrical Engineering
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The proposed approach relies on the application of Ambient Intelligence (AmI) technologies and a new method for the detection of abnormal human behaviors in a controlled environment. ...
When eating disorders coexist with other mental health disorders, eating disorders often go undiagnosed and untreated; a low number of sufferers obtain treatment for the eating disorder. ...
The main contribution of this paper, however, is a new method for the modeling and detection of abnormal human behaviors. ...
doi:10.1007/978-94-007-5086-9_22
fatcat:qtp5smilefc5fgt6adwy5u24oy
Enhanced Approach Using Reduced SBTFD Features and Modified Individual Behavior Estimation for Crowd Condition Prediction
2019
Entropy
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The basic context-aware framework (BCF) uses activity recognition based on emerging intelligent technology and is among the best that has been proposed for this purpose. ...
This article reports our work on the development of an enhanced context-aware framework (EHCAF) using smartphone participatory sensing for crowd monitoring, dimensionality reduction of statistical-based ...
This was realized using the CCS, which triggers up a context-aware alert to predict the abnormal behavior of an individual and crowd condition. ...
doi:10.3390/e21050487
pmid:33267201
fatcat:6wyrxk6ezzcgfpkst3q6d3t6ge
Towards a Novel Analysis Approach for Collaborative Ubiquitous Systems
2012
2012 IEEE 21st International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises
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A promising solution consists of developing context aware applications which automatically change their behavior according to the user needs, the available resources and the surrounding environment. ...
In this paper, we focus on the second phase and we propose an analysis approach of collaborative ubiquitous systems which aims at analyzing context information and detecting significant abnormal changes ...
Indeed, in this family, peaks characterize sudden changes form a normal behavior to an abnormal one. ...
doi:10.1109/wetice.2012.21
dblp:conf/wetice/KhabouR12
fatcat:juhgjgvoyndbvnqoaoskkvy5fy
A Review on Scaling Mobile Sensing Platforms for Human Activity Recognition: Challenges and Recommendations for Future Research
2020
IoT
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This review paper contributes to raising awareness of challenges faced today by mobile sensing platforms that perform learning and behavior inference with respect to human routines: how current solutions ...
The paper provides a set of guidelines that contribute to a better functional design of mobile sensing infrastructures, keeping scalability as well as interoperability in mind. ...
With automatic context recognition, it is possible, for instance, to detect abnormal patterns, e.g., isolation of a user, falls, etc. [92] [93] [94] . ...
doi:10.3390/iot1020025
fatcat:j5doqye55bfa3oj6derzmszsha
A predictive approach for efficient e-Health monitoring
2015
2015 17th International Conference on E-health Networking, Application & Services (HealthCom)
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We intend to combine a good optimization of the resources (e.g. network and energy) and an automatic evaluation of the person's dependency while ensuring a high accuracy for detecting unusual behaviors ...
The proposed system considers the person's context and predicts the health condition based on the usual behavior and energy consumption for each daily activity. ...
We propose a predictive and context-aware monitoring system able to collect relevant and contextual data, detect abnormal behaviors and evaluate the person's dependency while remaining cost-efficient. ...
doi:10.1109/healthcom.2015.7454510
dblp:conf/healthcom/MshaliLM15
fatcat:bwtjwu4tujb6pncfljia27ugqq
RFID-Based Human Behavior Modeling and Anomaly Detection for Elderly Care
2010
Mobile Information Systems
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This research aimed at building an intelligent system that can detect abnormal behavior for the elderly at home. ...
With the movement data (RSSI values), the clustering technique is then used to build a personalized model of normal behavior. ...
The goal for such modeling is to detect abnormal behaviors. ...
doi:10.1155/2010/460103
fatcat:rpnsvotwejgchh7i23ht3dgoxa
Crowd Monitoring and Localization Using Deep Convolutional Neural Network: A Review
2020
Applied Sciences
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Developing a robust crowd monitoring system (CMS) is a challenging task as it involves addressing many key issues such as density variation, irregular distribution of objects, occlusions, pose estimation ...
Therefore, many researchers have turned towards computer vision and machine learning that have overcome these issues by minimizing the need of human involvement. ...
Acknowledgments: The authors extend their appreciation to the Deputyship for Research and Innovation, Ministry of Education in Saudi Arabia for funding this research work through the project number QURDO001 ...
doi:10.3390/app10144781
fatcat:i7x5c6sdo5cdrfwtrszsdvixsm
Cyber–physical systems and context-aware sensing and computing
2017
Computer Networks
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) which is human behavior. ...
associated with CPS and context aware sensing. ...
doi:10.1016/j.comnet.2017.02.012
fatcat:nwox4zlqz5hxbizv6rfpgdd2sy
Towards Modeling the Behavior of Autonomous Systems and Humans for Trusted Operations
[chapter]
2016
Robust Intelligence and Trust in Autonomous Systems
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For example, flexible autonomous platforms deployed in a range of environments place a burden on humans to understand evolving behaviors. ...
A supervisory control paradigm can reduce workload and allow a single human to manage multiple autonomous platforms. ...
A key aspect of using normalcy models for detecting abnormal behaviors is the notion of context; and behaviors should be understood in the context in which they occur. ...
doi:10.1007/978-1-4899-7668-0_2
fatcat:t42fhspaqverlb63bollcmriva
Daily Living Activity Recognition In-The-Wild: Modeling and Inferring Activity-Aware Human Contexts
2022
Electronics
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The proposed scheme offers a detailed/fine-grained representation of natural human activities with contexts, which is crucial for modeling human-environment interactions in context-aware applications/systems ...
Therefore, in addition to physical activity recognition, it is also vital to model and infer the user's context information to realize human-environment interactions in a better way. ...
Thus, the proposed scheme can also be extended to detect/recognize normal and abnormal human behavior for predicting health-related risks. ...
doi:10.3390/electronics11020226
fatcat:cqykt235grcv3bn2i6wfzexwyy
Context-Aware Healthcare Adaptation Model for COPD Diseases
[chapter]
2020
Lecture Notes in Computer Science
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In this article, we are combining the healthcare telemonitoring systems with the context awareness and self-adaptation paradigm to provide a self-adaptive framework architecture for COPD patients. ...
These systems have the ability to self-adapt to meet changes in their execution environment and the user's context. ...
factors and detect suitable action in an abnormal situation. ...
doi:10.1007/978-3-030-51517-1_27
fatcat:7dh2usgsbze6tp3brz34tdrczy
Application of Machine Learning-Based Pattern Recognition in IoT Devices: Review
[chapter]
2021
Proceedings of International Joint Conference on Computational Intelligence
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2022 pre-print arXiv:2202.02456v1 fatcat:mwwbfsvjcbfhxf5owhuoxvkt4y
After reviewing the applications of different machine learning algorithms, results vary from case to case, but a general conclusion can be drawn that the optimal machine learning-based pattern recognition ...
With greater numbers of everyday objects being connected to the Internet, many different innovations have been presented to make our everyday lives more straightforward. ...
ProFiOt: Abnormal Behavior Profiling (ABP) of IoT Devices Based on a Machine Learning Approach Using data from the Intel Berkeley Lab, a system was built to detect abnormal behavior in IoT devices using ...
doi:10.1007/978-981-16-3246-4_52
fatcat:ipb2x4ayhberbdctmfsgp475le
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