Massive gatherings require hosting authorities to plan and deploy extensive arrangements to facilitate attendees while considering crowd safety the core objective. The task becomes more challenging when crowd is diverse in terms of language, culture, ethics and age-group. Hajj is an annual event where more than 2 million pilgrims from all over the world, gather in Makkah Al-Mukarramah to perform a series of spatio-temporal rituals. To plan and execute the event, the management needs to understand the behavior of both individuals and groups of pilgrims belonging to different nationalities. In this paper, we proposed a big data framework that collects mobile sensory data from all pilgrims by providing them location-based context-aware services through a mobile application. We utilize the collected data to study pedestrians' flow rate, mobility patterns for individuals and groups and their behaviour and preferences during movement. The extracted information can be analyzed to propose solutions to crowd related challenges, including mobility schedules, crowd modelling and simulation and emergency evacuation plans.

Reduced cost and increased proliferation of sensors has resulted in the generation of a large amount of data. To make use of this data effectively, efficient techniques for collecting, storing and managing data are needed. In this paper, we present a health big data indexing technique that allows for the efficient storage, querying and management of tele-rehabilitation related big data collected via health sensors connected to client machines accessing web-based e-Health frameworks. Our novel scheme is based on indexing of rehabilitation data based on the human body joint model. We further index the data based on other parameters that may be of interest to researchers such as ethnicity and geographical location. We have described all components of the system in brief.

The proliferation of networked home appliances, coupled with the popularity of low cost gesture detection sensors has made it possible to create smart home environments where users can manipulate devices of daily use through gestures. In this paper, we present a multi-sensory environment that allows a disabled person to control actual devices around the house that are presented to her in a mixed reality environment, as part of occupational therapy exercises. An analytical engine processes the motion data collected by gesture recognition sensors, measures recovery metrics, such as joint range of motion and speed of movement, etc. and presents the results to the therapist or the patient in the form of graphs and exercise statistics. We have incorporated intuitive 2D and 3D user interfaces into the environment to make the therapy experience more engaging and immersive for the disabled people. From the multimedia occupational therapy exercise data analysis, a therapist can get determine the ability of a patient to perform daily life activities without the help of others.

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 spatio-temporal 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.

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.

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 spatio-temporal 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.

This paper presents a system that enables efficient and scalable real-time user and vehicle discovery using textual, audio and video mechanisms. The system allows users to group together for shared intra-city transportation with the aid of multimedia that helps individuals to 1) find community of common interest (CoCI), 2) locate individual users in a large crowd and 3) locate vehicles for mobility in an efficient and cost effective manner. The system is a pilot project and will be deployed during Hajj 2015 when over three million pilgrims from all over the world visit Makkah, Saudi Arabia.

In this paper, we present a novel idea of a map-based therapy environment for people with Hemiplegia. The therapy environment is designed according to the suggestions of therapists, which consists of a spatial map browsing serious game augmented with our novel multi-sensory natural user interface (NUI). The NUI is based on 3D motion sensors that can recognize different hand and body gestures used for browsing a 3D or 2D map. The 3D motion sensors work in a non-invasive way; hence, they do not require any wearable body attachments and can be used at home without assistance from the therapists. The map-browsing environment provides an immersive experience to the disabled users, which helps in performing therapy in an interesting and entertaining manner. We have developed analytics for measuring certain quality of health improvement metrics from each type of spatial map browsing movements. The 3D motion sensors have been tested with Nokia, Google, ESRI, and a number of other maps that allow a subject to visualize and browse the 3D and 2D maps of the world. The map browsing session data shows the nature of big data; hence, the session data is stored in a cloud environment. Our developed serious game environment is web-based; thus anyone having the appropriate low cost sensor hardware can plug it in and start experiencing a natural way of hands free map browsing. We have deployed our framework in a hospital that treats Hemiplegic patients. Based on the feedback obtained, the developed platform shows a huge potential for use in hospitals that provide physiotherapy services as well as at patients' home as an assistive therapeutic service.

Recently, the use of non-invasive ways to track joint motion in the human body has drawn significant attention in the therapy domain. One of the reasons for this popularity is due to availability of economically priced 3D motion sensors. In this paper, we present a web-based 3D interactive serious game interface that uses non-invasive methods to recognize the movements of the body. Motion data of a subject is collected through two motion sensors, a Kinect and a LEAP, in a non-invasive manner. Joint motion along with inverse kinematic joint information is displayed in 3D environment in a live manner or recorded for offline replaying and data analysis. To facilitate the complex therapy authoring process, the system incorporates an authoring tool that allows a therapist to design a complex therapy in terms of primitive therapies and assign it to a patient. The subject as well as other members of the community of interest such as therapists, parents and caregivers can view the results at any time and can follow up with patient's progress.

This paper presents a multimedia e-health framework to conduct therapy sessions by collecting live therapeutic data of patients in a non-invasive way. Using our proposed framework, a therapist can model complex gestures by mapping them to a set of primitive actions and generate high-level therapies. Two inexpensive 3D motion tracking sensors, a Kinect and a Leap, are used to collect motion data of a given subject. Data can then be displayed on screen in a live manner or recorded for offline replaying and analysis. The system incorporates an intelligent authoring tool for therapy design, and produces live plots that show the quality of improvement metrics for a given patient.

In this paper, we present an interactive multimedia environment that can be used to effectively complement the role of a therapist in the process of rehabilitation for disabled children. We use Microsoft Kinect 3D depth sensing camera with the online Second Life virtual world to record rehabilitation exercises performed by a physiotherapist or a disabled child. The exercise session can be played synchronously in Second Life. The physical activities of the users are synchronized with their virtual counterparts in the Second Life. The exercises can be recorded as well and made available for downloading to facilitate offline playback. A disabled child can follow the exercise at home in the absence of the therapist, since the system can provide visual guidance for performing the exercise in the right manner. Using the proposed system, parents at home can also assist the disabled child in performing therapy sessions in the absence of a therapist. Following the suggestions of therapists, the developed prototype can track several gestures of children who have mobility problems. Using a single Kinect device, we can capture high resolution joint movement of the body, without the need for any complicated hardware set up. The initial joint-based angular measurements show promising potential of our prototype to be deployed in real physiotherapy sessions.