Faizan Rehman | Umm Al-Qura University, Makkah, Saudi Arabia (original) (raw)
Papers by Faizan Rehman
Thèse dirigée par Ahmed LBATH préparée au sein du Laboratoire d'Informatique de Grenoble (LIG) da... more Thèse dirigée par Ahmed LBATH préparée au sein du Laboratoire d'Informatique de Grenoble (LIG) dans l'École Doctorale Mathematiques, Sciences et Technologies de l'Information, Informatique (EDMSTII) Vers une plateforme pour l'extraction et la visualisation multi-échelle d'événements sociaux Towards a Framework for Multiscale Social Event Extraction and Visualization Thèse soutenue publiquement le 7 December 2018, devant le jury composé de:
Journal of King Saud University - Computer and Information Sciences, 2023
Computers, Materials & Continua
The Lancet Child & Adolescent Health, 2022
BACKGROUND Disability and mortality burden of non-communicable diseases (NCDs) have risen worldwi... more BACKGROUND Disability and mortality burden of non-communicable diseases (NCDs) have risen worldwide; however, the NCD burden among adolescents remains poorly described in the EU. METHODS Estimates were retrieved from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. Causes of NCDs were analysed at three different levels of the GBD 2019 hierarchy, for which mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) were extracted. Estimates, with the 95% uncertainty intervals (UI), were retrieved for EU Member States from 1990 to 2019, three age subgroups (10-14 years, 15-19 years, and 20-24 years), and by sex. Spearman's correlation was conducted between DALY rates for NCDs and the Socio-demographic Index (SDI) of each EU Member State. FINDINGS In 2019, NCDs accounted for 86·4% (95% uncertainty interval 83·5-88·8) of all YLDs and 38·8% (37·4-39·8) of total deaths in adolescents aged 10-24 years. For NCDs in this age group, neoplasms were the leading causes of both mortality (4·01 [95% uncertainty interval 3·62-4·25] per 100 000 population) and YLLs (281·78 [254·25-298·92] per 100 000 population), whereas mental disorders were the leading cause for YLDs (2039·36 [1432·56-2773·47] per 100 000 population) and DALYs (2040·59 [1433·96-2774·62] per 100 000 population) in all EU Member States, and in all studied age groups. In 2019, among adolescents aged 10-24 years, males had a higher mortality rate per 100 000 population due to NCDs than females (11·66 [11·04-12·28] vs 7·89 [7·53-8·23]), whereas females presented a higher DALY rate per 100 000 population due to NCDs (8003·25 [5812·78-10 701·59] vs 6083·91 [4576·63-7857·92]). From 1990 to 2019, mortality rate due to NCDs in adolescents aged 10-24 years substantially decreased (-40·41% [-43·00 to -37·61), and also the YLL rate considerably decreased (-40·56% [-43·16 to -37·74]), except for mental disorders (which increased by 32·18% [1·67 to 66·49]), whereas the YLD rate increased slightly (1·44% [0·09 to 2·79]). Positive correlations were observed between DALY rates and SDIs for substance use disorders (rs=0·58, p=0·0012) and skin and subcutaneous diseases (rs=0·45, p=0·017), whereas negative correlations were found between DALY rates and SDIs for cardiovascular diseases (rs=-0·46, p=0·015), neoplasms (rs=-0·57, p=0·0015), and sense organ diseases (rs=-0·61, p=0·0005). INTERPRETATION NCD-related mortality has substantially declined among adolescents in the EU between 1990 and 2019, but the rising trend of YLL attributed to mental disorders and their YLD burden are concerning. Differences by sex, age group, and across EU Member States highlight the importance of preventive interventions and scaling up adolescent-responsive health-care systems, which should prioritise specific needs by sex, age, and location. FUNDING Bill & Melinda Gates Foundation.
International Journal of Advanced Computer Science and Applications, 2020
Traffic analysis of vehicles in densely populated areas and places of public gathering can provid... more Traffic analysis of vehicles in densely populated areas and places of public gathering can provide interesting insights into crowd behavior. Hajj is a spatio-temporally bound religious activity that is held annually and attended by more than 2 million people. More than 17,000 buses are used to transport pilgrims on fixed days to fixed locations. This poses great challenges in terms of crowd management. Using Global Positioning System (GPS) and Automatic Vehicle Location (AVL) sensors attached to buses, a large amount of spatiotemporal vehicle data can be collected for traffic analysis. In this paper, we present a study whereby driver behavior was extracted from an analysis of vehicle big data. We have explained in detail how we collected data, cleaned it, moved it to a big data repository, processed it and extracted information that helped us characterize driver behavior according to our definition of aggressiveness. We have used data from 17,000 buses that has been collected during Hajj 2018.
2015 4th International Conference on Advanced Computer Science Applications and Technologies (ACSAT), 2015
Many real world complex networks from different domains share a common property that their node c... more Many real world complex networks from different domains share a common property that their node connectivity shows a scale-free power law behavior. In such networks, highly connected nodes (Hubs) are widely believed to have special importance in network management. In this paper, we discuss an environment whereby members of a very large crowd gathered to perform spatio-temporal activities, interact with different services and with one another to form a network of interest. The context of users is captured through smartphones and is processed by a cloud based framework to identify the aforementioned Hubs. We show that initial results exhibit Scale Free Network (SFN) behavior that can be further utilized for instant diffusion of important messages within the network through successive allocation of Hubs. We will focus on two basic network analysis metrics, in particular, degree of nodes and their weighted links. We will show that weighted links are closer to have a SFN behavior. We also plan to validate the effectiveness of our proposed SFN crowd behavior during next year Hajj, where millions of pilgrims will get together to perform religious rituals.
Proceedings of the 1st ACM SIGSPATIAL Workshop on Analytics for Local Events and News, 2017
The age-old practice of cartography has undergone fundamental shifts with the advent of the digit... more The age-old practice of cartography has undergone fundamental shifts with the advent of the digital age. Today's digital maps are often crowd-sourced, allow interactive route planning, and may contain live updates, such as traffic congestion state. In this paper, we take the concept of maps one step further by introducing a new generation of maps, which contain the additional functionality of showing multi-resolution spatio-temporal events, extracted dynamically from social media streams. Building such maps requires developing a scalable and efficient system to deal with a variety of unstructured data streams, applying sentiment analysis and multi-dimensional clustering techniques to extract relevant Events of Interest (EoI) at different map scales, and inferring the spatio-temporal scope of detected events. This paper presents a novel system that extracts events from social data at different levels of spatio-temporal granularities. The system implements a hierarchical in-memory spatio-temporal indexing scheme to support efficient access to data streams, as well as for memory flushing purposes. Data streams are first processed to extract events at a local scale. Next, we determine the proper spatio-temporal scope and the level of abstraction for detected events at a global scale. This allows us to show live multi-resolution events in correspondence to the scale of the view -- when viewing at a city scale, we see events of higher significance, while zooming in to a neighborhood highlights events of a more local interest.
2015 IEEE/ACS 12th International Conference of Computer Systems and Applications (AICCSA), 2015
Recommending an optimized path for a large crowd poses a unique challenge to existing routing alg... more Recommending an optimized path for a large crowd poses a unique challenge to existing routing algorithms due to the interactions between users and the dynamic changes over road networks. Industries, researchers and end users show an enormous interest in crowdsourced data comprising social networks and user-generated content to remain updated with their concerns. In this paper, we present a data collection framework that helps users to find optimized routes in a dynamic environment. We have developed a data collection framework to collect dynamic road conditions via a set of location-based services to support a very large Hajj crowd by capturing their locations using smartphones. We also collect geotagged social network data that provides more details about road conditions. The system leverages geotagged crowdsourced information to identify constraints such as accidents, congestions, and roadblocks. Moreover, by continuously collecting real-time geotagged data of moving users, the system can also find the flow of traffic and road conditions. We propose a spatial grid index to compute the optimized path, and to identify the affected users within impact zones. The plan is to test the whole application and back-end server during Hajj 2016, where over three million pilgrims from all over the world gather to perform their rituals.
Intelligent Automation & Soft Computing, 2022
Behaviour & Information Technology, 2018
Crowdsourcing offers great opportunities to recognise user context and prescribe relevant service... more Crowdsourcing offers great opportunities to recognise user context and prescribe relevant services for both offline and real-time activities. In this work, we present a zoning model that leverages spatio-temporal dimensions and then employs different contexts to recommend necessary customised services. The context model takes into consideration three context sets: fully restricted, fully unrestricted and semi-restricted with respect to both spatial and temporal Scale Free Network Analysis of a Large Crowd through Their Spatio-Temporal Activities
SIGSPATIAL Special, 2016
As human-centered interactive technologies, serious games are getting popularity in a variety of ... more As human-centered interactive technologies, serious games are getting popularity in a variety of fields such as training simulations, health, national defense, and education. To build the best learning experience when designing a serious game, a system requires the integration of accurate spatio-temporal information. Also, there is an increasing need for intelligent medical technologies, which enable patients to live independently at home. This paper introduces a novel e-Health framework that leverages GIS-based serious games for people with disabilities. This framework consists of a spatio-temporal map-browsing environment augmented with our newly introduced multi-sensory natural user interface. We propose a comprehensive architecture that includes a sensory data manager, a storage layer, an information processing and computational intelligence layer, and a user interface layer. Detailed mathematical modeling as well as mapping methodology to convert different therapy-based hand-ge...
Proceedings of the 23rd ACM international conference on Multimedia, 2015
Aggregating interesting spatio-temporal events of daily life in a diary used to be favorite pasti... more Aggregating interesting spatio-temporal events of daily life in a diary used to be favorite pastime for many individuals. However, crescive use of social media through portable digital devices is replacing traditional diary writing. Thanks to ubiquity of smartphones, people can now add multiple media types in order to record joyful moments and events with a time line. In this paper, we propose a spatio-temporal multimedia authoring tool by leveraging the ubiquity of geo-tagged multimedia that represents activities of interest to the user and allowing users to aggregate the multimedia for generating a digital diary. The authoring tool allows users to aggregate one's own spatial media with that of publicly available geo-tagged multimedia artifacts. The complex digital diary can then be saved into a big data repository for personal use as well as for sharing with a community of interest (COI). During the authoring process, the system allows a novel visualization technique of browsing clustered multiple points of interests (CMPOI) at a single GPS location, thereby exploring POIs in a multi-story building, shopping mall, etc. To facilitate efficient and user friendly discovery of CMPOIs, the authoring environment also supports spatio-temporal multimedia queries such as range and KNN (K nearest neighbor) queries from the big data environment. We plan to incorporate this multimedia authoring tool with our existing large scale multimedia supported crowdsourcing environment that is envisioned to support millions of pilgrims during the Hajj 2015 event.
Proceedings of the 23rd ACM international conference on Multimedia, 2015
Logging on to a system using a conventional keyboard may not be feasible in certain environments,... more Logging on to a system using a conventional keyboard may not be feasible in certain environments, such as, in a surgical operation theatre or in an industrial manufacturing facility. We have developed a multi-sensory gesture based login system that allows a user to access secure information using body gestures. The system can be configured to use different types of gestures according to the type of sensors available to the user. We have proposed a simple scheme to represent all alphanumeric characters required for password entry as gestures within the multi-sensory environment. Our scheme is scalable enough to support sensors that detect a large number of gestures to those that can only accept a few. This allows the system to be used in a variety of situations such as usage by disabled persons with limited ability to perform gestures. We are in the midst of deploying our developed system in a clinical environment.
Proceedings of the 23rd ACM international conference on Multimedia, 2015
Traditional routing algorithms for calculating the fastest or shortest path become ineffective or... more Traditional routing algorithms for calculating the fastest or shortest path become ineffective or difficult to use when both source and destination are dynamic or unknown. To solve the problem, we propose a novel semantic routing system that leverages geo-tagged rich crowdsourced multimedia information such as images, audio, video and text to add semantics to the conventional routing. Our proposed system includes a Semantic Multimedia Routing Algorithm (SMRA) that uses an indexed spatial big data environment to answer multimedia spatiotemporal queries in real-time. The results are customized to the users' smartphone bandwidth and resolution requirements. The system has been designed to be able to handle a very large number of multimedia spatio-temporal requests at any given moment. A proof of concept of the system will be demonstrated through two scenarios. These are 1) multimedia enhanced routing and 2) finding lost individuals in a large crowd using multimedia. We plan to test the system's performance and usability during Hajj 2015, where over four million pilgrims from all over the world gather to perform their rituals.
Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2015
Social networks, such as Facebook, Instagram, and Twitter, provide intuitive ways to share a vari... more Social networks, such as Facebook, Instagram, and Twitter, provide intuitive ways to share a variety of information including geotagged multimedia data within users' communities of interest (COI) or publicly in real-time. Real-time geotagged multimedia data can provide semantics to conventional spatial queries in order to enrich the user navigation experience. In this paper, we introduce a mechanism to process spatio-temporal queries by leveraging geotagged multimedia data such as images, audio, video, and text, in order to add semantics to the conventional queries. Our framework collects, stores, and spatially tags multimedia data shared by users through social networks or through our developed mobile application. The system then uses such data in order to enhance the conventional routing services by resolving existing usability issues and by providing semantics to the routes in terms of enriched points of interest while taking dynamic road conditions into account. A proof of concept of the system will be demonstrated with the following spatio-temporal queries on road networks: 1) multimedia-enhanced shortest path queries; 2) multimedia-enhanced k-nearest neighbor queries; and 3) multimedia-enhanced range queries. Finally, a novel technique for finding lost individuals using geotagged multimedia data is also introduced. The results are tailor-made to the users' smartphone bandwidth and resolution requirements
2015 IEEE International Conference on Big Data (Big Data), 2015
Crowdsourced multimedia data poses several challenges when it is collected, stored, indexed, retr... more Crowdsourced multimedia data poses several challenges when it is collected, stored, indexed, retrieved, and visualized. Examples of crowd source multimedia data are social sensors, vehicle sensors, physical sensors, human sensors, etc. Analyzing such multimodal and diversified crowdsourced data provides very rich understanding about the need of individuals within a crowd. Such understanding makes it possible to tailor services to individuals' needs, also called context-aware services. In this paper, we propose a spatial multimedia big data framework that can collect multimedia data from 1) a very large crowd equipped with multi-sensory smartphones, 2) vehicles, and 3) social networks. A set of multimedia services are offered to users to support their spatio-temporal activities. These include but not limited to 1) simple user interfaces to utilize multimedia services for instant guidance, 2) navigation to points of interests (POI), and 3) efficient and cost effective intra-city rides to users. The big data framework is designed to handle a very large number of multimedia spatio-temporal queries in real-time. The system is a pilot project and will be deployed during the event of Hajj 2015 when over three million pilgrims from all over the world will visit Makkah, Saudi Arabia to perform their Hajj rituals.
Proceedings of the 7th ACM SIGSPATIAL International Workshop on Computational Transportation Science - IWCTS '14, 2014
ABSTRACT With the advancement of mobile technologies, more and more people are connected to socia... more ABSTRACT With the advancement of mobile technologies, more and more people are connected to social networks such as Face-book and Twitter. Social networks allow users to share diversity of information including spatio-temporal data either publicly or within their community of interest in real-time. Particularly, by analyzing social network data streams and then validating the content, one can extract knowledge about dynamic road conditions for a given city. This paper presents a dynamic path recommender system that helps users finding optimized routes in dynamic environments based on social network data. The system collects geo-tagged social network data from which relevant knowledge is extracted for identifying constraints such as accidents , weather conditions, and congestions. Moreover, by continuously collecting moving user's geo-tagged data, the system can also identify the traffic flow as well as roads' conditions. As soon as the system identifies and validates a given constraint, it can notify affected users and recommend an adapted route from their current position to the destination. A proof of concept of the system will be shown through three example scenarios.
This paper discusses the next generation of digital maps, by positing that maps in future will in... more This paper discusses the next generation of digital maps, by positing that maps in future will intelligently self-update themselves based on distinctive events extracted dynamically from social media streams or other crowd-sourced data. To realize this concept, the challenges include developing a scalable and efficient system to deal with a variety of unstructured data streams, applying NLP and clustering techniques to extract relevant information from these streams, and inferring the spatio-temporal scope of detected events. This paper demonstrates Hadath, a system that extracts live events from social data by encapsulating incoming unstructured data into generic data packets. The system implements a hierarchical in-memory indexing scheme to support efficient access to data packets, as well as for memory flushing purposes. Data packets are then processed to extract Events of Interest (EoI), based on a multi-dimensional clustering technique. Next, we establish the spatial scope and ...
In today's busy world, users and authorities require better services to achieve their daily a... more In today's busy world, users and authorities require better services to achieve their daily activities and tasks in a smart way by using available resources in an optimized manner. The variety of available data sources, starting from crowdsourced data, open governmental data, and other online sources can provide users with smart tools to better manage their daily activities. However, collecting and integrating this multitude of overlapping data sources is a challenging task. Particularly, digital maps are being extensively used to browse and share information about points of interest, plan trips, and to find optimized paths. Within this context, there is a real opportunity to enrich traditional maps with different knowledge-based layers extracted from the variety of available data sources. This paper introduces the concept of "smart maps" by collecting, managing, and integrating heterogeneous data sources in order to infer relevant knowledge-based layers. Unlike conven...
As human-centered interactive technologies, serious games are get-ting popularity in a variety of... more As human-centered interactive technologies, serious games are get-ting popularity in a variety of fields such as training simulations, health, national defense, and education. To build the best learning experience when designing a serious game, a system requires the integration of accurate spatio-temporal information. Also, there is an increasing need for intelligent medical technologies, which enable patients to live independently at home. This paper introduces a novel e-Health framework that leverages GIS-based serious games for people with disabilities. This framework consists of a spatial map-browsing environment augmented with our newly introduced multi-sensory Natural User Interface. We propose a comprehensive architecture that includes a sensory data manager, a storage layer, an information processing and computational intelligence layer, and a user interface layer. Detailed mathematical modeling as well as map-
Thèse dirigée par Ahmed LBATH préparée au sein du Laboratoire d'Informatique de Grenoble (LIG) da... more Thèse dirigée par Ahmed LBATH préparée au sein du Laboratoire d'Informatique de Grenoble (LIG) dans l'École Doctorale Mathematiques, Sciences et Technologies de l'Information, Informatique (EDMSTII) Vers une plateforme pour l'extraction et la visualisation multi-échelle d'événements sociaux Towards a Framework for Multiscale Social Event Extraction and Visualization Thèse soutenue publiquement le 7 December 2018, devant le jury composé de:
Journal of King Saud University - Computer and Information Sciences, 2023
Computers, Materials & Continua
The Lancet Child & Adolescent Health, 2022
BACKGROUND Disability and mortality burden of non-communicable diseases (NCDs) have risen worldwi... more BACKGROUND Disability and mortality burden of non-communicable diseases (NCDs) have risen worldwide; however, the NCD burden among adolescents remains poorly described in the EU. METHODS Estimates were retrieved from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. Causes of NCDs were analysed at three different levels of the GBD 2019 hierarchy, for which mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) were extracted. Estimates, with the 95% uncertainty intervals (UI), were retrieved for EU Member States from 1990 to 2019, three age subgroups (10-14 years, 15-19 years, and 20-24 years), and by sex. Spearman's correlation was conducted between DALY rates for NCDs and the Socio-demographic Index (SDI) of each EU Member State. FINDINGS In 2019, NCDs accounted for 86·4% (95% uncertainty interval 83·5-88·8) of all YLDs and 38·8% (37·4-39·8) of total deaths in adolescents aged 10-24 years. For NCDs in this age group, neoplasms were the leading causes of both mortality (4·01 [95% uncertainty interval 3·62-4·25] per 100 000 population) and YLLs (281·78 [254·25-298·92] per 100 000 population), whereas mental disorders were the leading cause for YLDs (2039·36 [1432·56-2773·47] per 100 000 population) and DALYs (2040·59 [1433·96-2774·62] per 100 000 population) in all EU Member States, and in all studied age groups. In 2019, among adolescents aged 10-24 years, males had a higher mortality rate per 100 000 population due to NCDs than females (11·66 [11·04-12·28] vs 7·89 [7·53-8·23]), whereas females presented a higher DALY rate per 100 000 population due to NCDs (8003·25 [5812·78-10 701·59] vs 6083·91 [4576·63-7857·92]). From 1990 to 2019, mortality rate due to NCDs in adolescents aged 10-24 years substantially decreased (-40·41% [-43·00 to -37·61), and also the YLL rate considerably decreased (-40·56% [-43·16 to -37·74]), except for mental disorders (which increased by 32·18% [1·67 to 66·49]), whereas the YLD rate increased slightly (1·44% [0·09 to 2·79]). Positive correlations were observed between DALY rates and SDIs for substance use disorders (rs=0·58, p=0·0012) and skin and subcutaneous diseases (rs=0·45, p=0·017), whereas negative correlations were found between DALY rates and SDIs for cardiovascular diseases (rs=-0·46, p=0·015), neoplasms (rs=-0·57, p=0·0015), and sense organ diseases (rs=-0·61, p=0·0005). INTERPRETATION NCD-related mortality has substantially declined among adolescents in the EU between 1990 and 2019, but the rising trend of YLL attributed to mental disorders and their YLD burden are concerning. Differences by sex, age group, and across EU Member States highlight the importance of preventive interventions and scaling up adolescent-responsive health-care systems, which should prioritise specific needs by sex, age, and location. FUNDING Bill & Melinda Gates Foundation.
International Journal of Advanced Computer Science and Applications, 2020
Traffic analysis of vehicles in densely populated areas and places of public gathering can provid... more Traffic analysis of vehicles in densely populated areas and places of public gathering can provide interesting insights into crowd behavior. Hajj is a spatio-temporally bound religious activity that is held annually and attended by more than 2 million people. More than 17,000 buses are used to transport pilgrims on fixed days to fixed locations. This poses great challenges in terms of crowd management. Using Global Positioning System (GPS) and Automatic Vehicle Location (AVL) sensors attached to buses, a large amount of spatiotemporal vehicle data can be collected for traffic analysis. In this paper, we present a study whereby driver behavior was extracted from an analysis of vehicle big data. We have explained in detail how we collected data, cleaned it, moved it to a big data repository, processed it and extracted information that helped us characterize driver behavior according to our definition of aggressiveness. We have used data from 17,000 buses that has been collected during Hajj 2018.
2015 4th International Conference on Advanced Computer Science Applications and Technologies (ACSAT), 2015
Many real world complex networks from different domains share a common property that their node c... more Many real world complex networks from different domains share a common property that their node connectivity shows a scale-free power law behavior. In such networks, highly connected nodes (Hubs) are widely believed to have special importance in network management. In this paper, we discuss an environment whereby members of a very large crowd gathered to perform spatio-temporal activities, interact with different services and with one another to form a network of interest. The context of users is captured through smartphones and is processed by a cloud based framework to identify the aforementioned Hubs. We show that initial results exhibit Scale Free Network (SFN) behavior that can be further utilized for instant diffusion of important messages within the network through successive allocation of Hubs. We will focus on two basic network analysis metrics, in particular, degree of nodes and their weighted links. We will show that weighted links are closer to have a SFN behavior. We also plan to validate the effectiveness of our proposed SFN crowd behavior during next year Hajj, where millions of pilgrims will get together to perform religious rituals.
Proceedings of the 1st ACM SIGSPATIAL Workshop on Analytics for Local Events and News, 2017
The age-old practice of cartography has undergone fundamental shifts with the advent of the digit... more The age-old practice of cartography has undergone fundamental shifts with the advent of the digital age. Today's digital maps are often crowd-sourced, allow interactive route planning, and may contain live updates, such as traffic congestion state. In this paper, we take the concept of maps one step further by introducing a new generation of maps, which contain the additional functionality of showing multi-resolution spatio-temporal events, extracted dynamically from social media streams. Building such maps requires developing a scalable and efficient system to deal with a variety of unstructured data streams, applying sentiment analysis and multi-dimensional clustering techniques to extract relevant Events of Interest (EoI) at different map scales, and inferring the spatio-temporal scope of detected events. This paper presents a novel system that extracts events from social data at different levels of spatio-temporal granularities. The system implements a hierarchical in-memory spatio-temporal indexing scheme to support efficient access to data streams, as well as for memory flushing purposes. Data streams are first processed to extract events at a local scale. Next, we determine the proper spatio-temporal scope and the level of abstraction for detected events at a global scale. This allows us to show live multi-resolution events in correspondence to the scale of the view -- when viewing at a city scale, we see events of higher significance, while zooming in to a neighborhood highlights events of a more local interest.
2015 IEEE/ACS 12th International Conference of Computer Systems and Applications (AICCSA), 2015
Recommending an optimized path for a large crowd poses a unique challenge to existing routing alg... more Recommending an optimized path for a large crowd poses a unique challenge to existing routing algorithms due to the interactions between users and the dynamic changes over road networks. Industries, researchers and end users show an enormous interest in crowdsourced data comprising social networks and user-generated content to remain updated with their concerns. In this paper, we present a data collection framework that helps users to find optimized routes in a dynamic environment. We have developed a data collection framework to collect dynamic road conditions via a set of location-based services to support a very large Hajj crowd by capturing their locations using smartphones. We also collect geotagged social network data that provides more details about road conditions. The system leverages geotagged crowdsourced information to identify constraints such as accidents, congestions, and roadblocks. Moreover, by continuously collecting real-time geotagged data of moving users, the system can also find the flow of traffic and road conditions. We propose a spatial grid index to compute the optimized path, and to identify the affected users within impact zones. The plan is to test the whole application and back-end server during Hajj 2016, where over three million pilgrims from all over the world gather to perform their rituals.
Intelligent Automation & Soft Computing, 2022
Behaviour & Information Technology, 2018
Crowdsourcing offers great opportunities to recognise user context and prescribe relevant service... more Crowdsourcing offers great opportunities to recognise user context and prescribe relevant services for both offline and real-time activities. In this work, we present a zoning model that leverages spatio-temporal dimensions and then employs different contexts to recommend necessary customised services. The context model takes into consideration three context sets: fully restricted, fully unrestricted and semi-restricted with respect to both spatial and temporal Scale Free Network Analysis of a Large Crowd through Their Spatio-Temporal Activities
SIGSPATIAL Special, 2016
As human-centered interactive technologies, serious games are getting popularity in a variety of ... more As human-centered interactive technologies, serious games are getting popularity in a variety of fields such as training simulations, health, national defense, and education. To build the best learning experience when designing a serious game, a system requires the integration of accurate spatio-temporal information. Also, there is an increasing need for intelligent medical technologies, which enable patients to live independently at home. This paper introduces a novel e-Health framework that leverages GIS-based serious games for people with disabilities. This framework consists of a spatio-temporal map-browsing environment augmented with our newly introduced multi-sensory natural user interface. We propose a comprehensive architecture that includes a sensory data manager, a storage layer, an information processing and computational intelligence layer, and a user interface layer. Detailed mathematical modeling as well as mapping methodology to convert different therapy-based hand-ge...
Proceedings of the 23rd ACM international conference on Multimedia, 2015
Aggregating interesting spatio-temporal events of daily life in a diary used to be favorite pasti... more Aggregating interesting spatio-temporal events of daily life in a diary used to be favorite pastime for many individuals. However, crescive use of social media through portable digital devices is replacing traditional diary writing. Thanks to ubiquity of smartphones, people can now add multiple media types in order to record joyful moments and events with a time line. In this paper, we propose a spatio-temporal multimedia authoring tool by leveraging the ubiquity of geo-tagged multimedia that represents activities of interest to the user and allowing users to aggregate the multimedia for generating a digital diary. The authoring tool allows users to aggregate one's own spatial media with that of publicly available geo-tagged multimedia artifacts. The complex digital diary can then be saved into a big data repository for personal use as well as for sharing with a community of interest (COI). During the authoring process, the system allows a novel visualization technique of browsing clustered multiple points of interests (CMPOI) at a single GPS location, thereby exploring POIs in a multi-story building, shopping mall, etc. To facilitate efficient and user friendly discovery of CMPOIs, the authoring environment also supports spatio-temporal multimedia queries such as range and KNN (K nearest neighbor) queries from the big data environment. We plan to incorporate this multimedia authoring tool with our existing large scale multimedia supported crowdsourcing environment that is envisioned to support millions of pilgrims during the Hajj 2015 event.
Proceedings of the 23rd ACM international conference on Multimedia, 2015
Logging on to a system using a conventional keyboard may not be feasible in certain environments,... more Logging on to a system using a conventional keyboard may not be feasible in certain environments, such as, in a surgical operation theatre or in an industrial manufacturing facility. We have developed a multi-sensory gesture based login system that allows a user to access secure information using body gestures. The system can be configured to use different types of gestures according to the type of sensors available to the user. We have proposed a simple scheme to represent all alphanumeric characters required for password entry as gestures within the multi-sensory environment. Our scheme is scalable enough to support sensors that detect a large number of gestures to those that can only accept a few. This allows the system to be used in a variety of situations such as usage by disabled persons with limited ability to perform gestures. We are in the midst of deploying our developed system in a clinical environment.
Proceedings of the 23rd ACM international conference on Multimedia, 2015
Traditional routing algorithms for calculating the fastest or shortest path become ineffective or... more Traditional routing algorithms for calculating the fastest or shortest path become ineffective or difficult to use when both source and destination are dynamic or unknown. To solve the problem, we propose a novel semantic routing system that leverages geo-tagged rich crowdsourced multimedia information such as images, audio, video and text to add semantics to the conventional routing. Our proposed system includes a Semantic Multimedia Routing Algorithm (SMRA) that uses an indexed spatial big data environment to answer multimedia spatiotemporal queries in real-time. The results are customized to the users' smartphone bandwidth and resolution requirements. The system has been designed to be able to handle a very large number of multimedia spatio-temporal requests at any given moment. A proof of concept of the system will be demonstrated through two scenarios. These are 1) multimedia enhanced routing and 2) finding lost individuals in a large crowd using multimedia. We plan to test the system's performance and usability during Hajj 2015, where over four million pilgrims from all over the world gather to perform their rituals.
Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2015
Social networks, such as Facebook, Instagram, and Twitter, provide intuitive ways to share a vari... more Social networks, such as Facebook, Instagram, and Twitter, provide intuitive ways to share a variety of information including geotagged multimedia data within users' communities of interest (COI) or publicly in real-time. Real-time geotagged multimedia data can provide semantics to conventional spatial queries in order to enrich the user navigation experience. In this paper, we introduce a mechanism to process spatio-temporal queries by leveraging geotagged multimedia data such as images, audio, video, and text, in order to add semantics to the conventional queries. Our framework collects, stores, and spatially tags multimedia data shared by users through social networks or through our developed mobile application. The system then uses such data in order to enhance the conventional routing services by resolving existing usability issues and by providing semantics to the routes in terms of enriched points of interest while taking dynamic road conditions into account. A proof of concept of the system will be demonstrated with the following spatio-temporal queries on road networks: 1) multimedia-enhanced shortest path queries; 2) multimedia-enhanced k-nearest neighbor queries; and 3) multimedia-enhanced range queries. Finally, a novel technique for finding lost individuals using geotagged multimedia data is also introduced. The results are tailor-made to the users' smartphone bandwidth and resolution requirements
2015 IEEE International Conference on Big Data (Big Data), 2015
Crowdsourced multimedia data poses several challenges when it is collected, stored, indexed, retr... more Crowdsourced multimedia data poses several challenges when it is collected, stored, indexed, retrieved, and visualized. Examples of crowd source multimedia data are social sensors, vehicle sensors, physical sensors, human sensors, etc. Analyzing such multimodal and diversified crowdsourced data provides very rich understanding about the need of individuals within a crowd. Such understanding makes it possible to tailor services to individuals' needs, also called context-aware services. In this paper, we propose a spatial multimedia big data framework that can collect multimedia data from 1) a very large crowd equipped with multi-sensory smartphones, 2) vehicles, and 3) social networks. A set of multimedia services are offered to users to support their spatio-temporal activities. These include but not limited to 1) simple user interfaces to utilize multimedia services for instant guidance, 2) navigation to points of interests (POI), and 3) efficient and cost effective intra-city rides to users. The big data framework is designed to handle a very large number of multimedia spatio-temporal queries in real-time. The system is a pilot project and will be deployed during the event of Hajj 2015 when over three million pilgrims from all over the world will visit Makkah, Saudi Arabia to perform their Hajj rituals.
Proceedings of the 7th ACM SIGSPATIAL International Workshop on Computational Transportation Science - IWCTS '14, 2014
ABSTRACT With the advancement of mobile technologies, more and more people are connected to socia... more ABSTRACT With the advancement of mobile technologies, more and more people are connected to social networks such as Face-book and Twitter. Social networks allow users to share diversity of information including spatio-temporal data either publicly or within their community of interest in real-time. Particularly, by analyzing social network data streams and then validating the content, one can extract knowledge about dynamic road conditions for a given city. This paper presents a dynamic path recommender system that helps users finding optimized routes in dynamic environments based on social network data. The system collects geo-tagged social network data from which relevant knowledge is extracted for identifying constraints such as accidents , weather conditions, and congestions. Moreover, by continuously collecting moving user's geo-tagged data, the system can also identify the traffic flow as well as roads' conditions. As soon as the system identifies and validates a given constraint, it can notify affected users and recommend an adapted route from their current position to the destination. A proof of concept of the system will be shown through three example scenarios.
This paper discusses the next generation of digital maps, by positing that maps in future will in... more This paper discusses the next generation of digital maps, by positing that maps in future will intelligently self-update themselves based on distinctive events extracted dynamically from social media streams or other crowd-sourced data. To realize this concept, the challenges include developing a scalable and efficient system to deal with a variety of unstructured data streams, applying NLP and clustering techniques to extract relevant information from these streams, and inferring the spatio-temporal scope of detected events. This paper demonstrates Hadath, a system that extracts live events from social data by encapsulating incoming unstructured data into generic data packets. The system implements a hierarchical in-memory indexing scheme to support efficient access to data packets, as well as for memory flushing purposes. Data packets are then processed to extract Events of Interest (EoI), based on a multi-dimensional clustering technique. Next, we establish the spatial scope and ...
In today's busy world, users and authorities require better services to achieve their daily a... more In today's busy world, users and authorities require better services to achieve their daily activities and tasks in a smart way by using available resources in an optimized manner. The variety of available data sources, starting from crowdsourced data, open governmental data, and other online sources can provide users with smart tools to better manage their daily activities. However, collecting and integrating this multitude of overlapping data sources is a challenging task. Particularly, digital maps are being extensively used to browse and share information about points of interest, plan trips, and to find optimized paths. Within this context, there is a real opportunity to enrich traditional maps with different knowledge-based layers extracted from the variety of available data sources. This paper introduces the concept of "smart maps" by collecting, managing, and integrating heterogeneous data sources in order to infer relevant knowledge-based layers. Unlike conven...
As human-centered interactive technologies, serious games are get-ting popularity in a variety of... more As human-centered interactive technologies, serious games are get-ting popularity in a variety of fields such as training simulations, health, national defense, and education. To build the best learning experience when designing a serious game, a system requires the integration of accurate spatio-temporal information. Also, there is an increasing need for intelligent medical technologies, which enable patients to live independently at home. This paper introduces a novel e-Health framework that leverages GIS-based serious games for people with disabilities. This framework consists of a spatial map-browsing environment augmented with our newly introduced multi-sensory Natural User Interface. We propose a comprehensive architecture that includes a sensory data manager, a storage layer, an information processing and computational intelligence layer, and a user interface layer. Detailed mathematical modeling as well as map-