Agent-Based Autonomic Semantic Context-Aware Platform for Smart Health Monitoring and Disease Detection

Nowadays, mobile applications have been widely used in various health and social domains. While there are large number of smart devices that connect and transmit their context data in free manner, these mobile applications have limitations regarding the increasing number of heterogeneous context data sent by devices, conducting the problem of identifying user-centric situations and providing services in real-time. Many smart mobile health systems were proposed to ensure context-aware personal health monitoring and diseases detection, while most of them are failed to ensure a right level of dynamicity and enough flexibility for assisting users everywhere, anytime, through widespread sensors and mobile devices. In fact, it becomes necessary to rethink a new way to minimize the response time combining competitive agents with semantic-based situation reasoning strategy. In this paper, we introduce a novel agent-based platform with three-layered ontology for the semantic description and parallel management of services selection approach dedicated to context-aware health mobile applications. In addition, we propose an innovative parallel services discovery and optimal selection process, which involved a set of filtered and classified semantic health multipath according to user’s context and preferences with consistent mobility of users and limited resources (low battery, processing capabilities, memory and others). Experimental results show the effectiveness of the proposed approach as it includes the semantic service information on cooperative agents. In addition, the proposed approach ensures fast response time and prolongs the continuity of the mobile application.

[1]  Khalil Drira,et al.  A semantic‐enabled and context‐aware monitoring system for the internet of medical things , 2020, Expert Syst. J. Knowl. Eng..

[2]  Raoul Praful Jetley,et al.  Engineering high confidence medical device software , 2009, SIGBED.

[3]  Philippe Roose,et al.  Kalimucho: middleware for mobile applications , 2014, SAC.

[4]  Adel Alti,et al.  Cloud semantic-based dynamic multimodal platform for building mhealth context-aware services , 2015, 2015 IEEE 11th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob).

[5]  Adel Alti,et al.  Autonomic Semantic-Based Context-Aware Platform for Mobile Applications in Pervasive Environments , 2016, Future Internet.

[6]  Ezendu Ariwa,et al.  User mobility and resource scheduling and management in fog computing to support IoT devices , 2017, 2017 Seventh International Conference on Innovative Computing Technology (INTECH).

[7]  Cheng-Chi Lee,et al.  Robust anonymous authentication protocol for health-care applications using wireless medical sensor networks , 2013, Multimedia Systems.

[8]  Richard Chbeir,et al.  MSSN-Onto: An ontology-based approach for flexible event processing in Multimedia Sensor Networks , 2020, Future Gener. Comput. Syst..

[9]  Anind K. Dey,et al.  Understanding and Using Context , 2001, Personal and Ubiquitous Computing.

[10]  Hamid Mcheick,et al.  Ontology-Based Model to Support Ubiquitous Healthcare Systems for COPD Patients , 2018, Electronics.

[11]  Philippe Roose,et al.  Kalimucho: software architecture for limited mobile devices , 2009, SIGBED.

[12]  Yolande Berbers,et al.  A Quality-aware Federated Framework for Smart Mobile Applications in the Cloud , 2014, ANT/SEIT.

[13]  Devesh Pratap Singh,et al.  BAKMP-IoMT: Design of Blockchain Enabled Authenticated Key Management Protocol for Internet of Medical Things Deployment , 2020, IEEE Access.

[14]  Giuseppe De Pietro,et al.  A smart mobile, self-configuring, context-aware architecture for personal health monitoring , 2018, Eng. Appl. Artif. Intell..