Presently, over a billion people, including children (or about 15% of the world’s population) have been estimated to be living with disabilities [1
]. The absence of or the presence of ineffective support services or tools can make people with disabilities (PWDs) overly dependent on their families, friends, and caregivers. As a result, they are prohibited from being economically active and socially included. In a university, to make PWDs economically independent and to provide them with a sense of inclusion, a PWD-friendly campus/environment is needed. It is very important for the designers to take into account all the possible users, their interactions among themselves as well as with the environment before developing any products or services. The user involvement at each and every phase of the development process helps the designers to accomplish the optimal requirements for the PWDs [2
]. A proper solution for disabled people on the university campus can be defined as the one which is universal, adaptable, heterogeneous, and user-centered. In fact, it should be able to make PWDs life easy and productive instead of being idle and frustrated. Moreover, increased information sharing within the university campus has a positive impact on the evolution of the knowledge as well as the innovative capabilities of the academic environment. It would also give rise to opportunities and prospects for new collaborative and enriched basic and applied research.
The advances in mobile and wireless technology, and the new concept of location-based services (LBS) together with Geographic Information Systems (GIS), have led to the introduction of the smart adaptive professional network that is required for the establishment of a successful eco-system. The accelerated rapid development of the wireless network and mobile computing technologies that are the driving forces behind the mobile information services for PWDs has become an appealing research topic. In particular, the LBSs on mobile devices can convey location-based information to individual users, thus helping the users (including the PWDs) to acquire helpful and adaptive information [3
]. Furthermore, the interactive LBSs enhance personalized and context-aware information communication, and maximize the gain from such dynamic information sharing by empowering the user with extended functionalities.
In this project, a unified interface has been designed to support the PWDs during their movement within the campus. This new approach uses the concept of GIS within the platform of wireless technologies and develops an interactive smart context-aware y to enhance information sharing, communication, and dissemination within the King Saud University campus. The interface has been designed to suit everybody on campus, including PWDs. The size of font, font color, window color, as well as the voice recognition used for controlling the users’ interface have been considered in the design and development according to the needs of the PWDs. Consideration of all of the above aspects led to the development of an information-intensive eco-system to support knowledge, creativity, and innovation within the multi-disciplinary environment.
The paper has been divided in six sections as follows. A literature review pertaining to GIS and sensors technologies has been conducted to determine the right solution for this project (as shown in Geographic Information System and Sensors Technologies). The interface has been designed in accordance with the specified criteria applicable to the impairment conditions of the majority of PWDs (as described in Design Consideration and Methodology). A review of the existing commercialized solutions has been performed to verify their compliance with the specified criteria, as well as to establish the direction of improvement, in order to maximize the PWD users’ satisfaction (as shown in the Interface Design consideration to Support PWD Needs). The complete design of the University-Based Smart and Context Aware Solution for People with Disabilities (USCAS-PWD) can be realized in the Group Design and Implementation Consideration. A description of the group selection for the PWDs to support the different impairment conditions has been presented in the implementation of the USCAS-PWD. An implementation of the Unified Interface has been described for the indoor (inside the building) and outdoor at the university campus within the section Implementation of the Unified Interface for Indoor Network. The event behavior algorithm and the movement direction algorithm are discussed within the algorithm section.
2. Geographic Information System and Sensors Technologies
With the continuous increase in online spatial data, the adaptation of spatial content according to the user’s context has become crucial. In addition, the introduction of GIS [4
] has changed the way geographical and spatial information is manipulated, accessed, and understood. For example, Li [5
] developed a conceptual model based on LBS to assist the urban pedestrian. The results of his study revealed the importance of user preferences on the information requirements. Similarly, Zipf [6
] and Yuxia [7
] presented several approaches to realize adaptive mobile GIS services in the domain of pedestrian navigation and tourist information. The Intelligent Map Agents (IMA) architecture developed by Gervais [8
] for GIS was aimed at superseding the monolithic approach through a new dynamic, lean, and customizable system supporting spatially-oriented applications. Relevant to the concept of the adaptive GIS, personalization, and context-awareness, Aoidh [9
] introduced an approach that implicitly monitored the user’s activity and generated a user profile reflecting her/his information preferences based on the interactions of the user with the system, and her/his physical location and movements. Brossard et al. [10
] have also proposed a solution allowing the context to be managed inside an application’s conceptual model, in order to provide more flexible web applications from the user’s point of view.
Recently, considerable interest has been shown in interactive LBS, specifically in the fields of mobile communications and wireless networking. For instance, Jung [11
] proposed an interactive approach by developing social networks between mobile users through collection of a datasets from about two million users. Chang et al. [12
], developed an adaptive context-aware recommendation system. The system was built using a slow intelligence approach. The system was implemented as an application on the smart phone. A case study in Pittsburg, USA was conducted, and the results obtained by the experimental campaign were satisfactory and showed good perspective of this kind of approach. Similarly, Rebollo-Monedero [13
] presented a novel protocol based on user collaboration to privately retrieve location-based information from an LBS provider. In their approach, the user queries, comprising accurate locations, remained unchanged, and the collaborative protocol did not impose any special requirements on the query–response function of the LBS. The application devised by Kbar [14
] enabled the user to conduct a search using a set of three modes: keyword, location, and targeted profile. The GIS was utilized within a platform of wireless technologies to develop an interactive smart context-aware GIS for a University. Until now, many technologies have been developed based on Global Positioning System (GPS) receivers and General Packet Radio Service GPRS transmitters, where the positions are stored and accessed via MySQL or web servers through internet connectivity [15
Different technologies, including WiFi tag through Access Point (AP) [18
], sensor technology based on wireless personal area network (WPAN) IEE 802.15.4 [19
], passive and active radio frequency identification (RFID) sensors, GPS technologies [20
], etc., can be employed in tracking user location. For example, Ning et al. [21
] introduced a tree-like code structure to develop a unified modeling scheme of the physical objects (in the RFID network) without an identification code. A hybrid platform which is based on the combination of RFID, WiFi, and GPS technologies showed better accuracy in comparison to the individual technologies [22
]. In the system developed by Dao et al. [22
], the user (with a smartphone) was detected by the RFID readers and the WiFi APs. Similarly, Li et al. [23
] developed a system based on radio-over-fiber (RoF) network involving the simultaneous transmission of RFID, Wi-Fi, and ZigBee services. They integrated all the wireless signals in the electrical domain, and then modulated them onto the optical carrier through an optical modulator. The system was tested over a 2 km RoF link where RFID, WiFi, and ZigBee master nodes could communicate effectively. Meanwhile, S. Szewcyzk [24
] analyzed the individual impairment behavior using machine learning techniques. They used inhabitant feedback to decrease the annotation time and improve their performance. In fact, the Wireless Body/Personal Area Network (WBPAN) developed by G. Yella Reddy [25
] included low-cost, light, and small sensors for continuous health monitoring and sending instantaneous feedback to the user.
Assistive technologies (ATs) can also be used to track and monitor the activity and vital signs of elder and motor-impaired individuals through different types of wearable sensors, implantable sensors, and microsystems that can be swallowed, such as microcapsule devices [26
]. Five basic features, including the automation, multi-functionality, adaptability, interactivity, and efficiency play a significant role in the design of smart homes [27
]. In order to help blind people to walk on the streets, Chen and Zhi [28
] proposed a solution based on sensors that detected the blind individual’s movement through an RFID tag installed on a cane. The walking path of the blind man was designed to incorporate the electronic tags underneath it. An indoor localization aid, called portable position and orientation estimation (POSE) was developed by Hesch and Roumeliotis [29
] for visually-impaired persons, in order to increase their safety and independence. The 3D orientation of the cane was tracked in the first layer through measurements using a three-axis gyroscope and laser scanner. The 2D position of the person was detected in the second layer using corner features extracted from the laser-scan data, linear velocity measurements from the pedometer, and a filtered version of the cane’s yaw. Kammoun et al. [30
] utilized micro-navigation (sensing immediate environments) and macro-navigation (reaching remote destinations) functions to design a system for blind people in indoor and outdoor environments. This system started searching for any object requested by the user in the captured images. After the object was detected, the system would direct the user to move their hand for grasping via voice command.
The multi-sensory (audio and force feedback) learning environment developed by Darrah [31
] was used to teach visually-impaired or blind children. It consisted of a PC, a low-cost force feedback stylus-based haptic device, auditory cues, and high contrast graphics. Similarly, the electronic navigation system [32
] could detect obstacles around the subject (visually-impaired and blind people) up to 500 cm in the front, left, and right directions through a network of ultrasonic sensors. Gallaghera et al. [33
] also designed and tested an indoor navigation system for visually-impaired persons. This system was based on the internal hardware of the smartphone (such as the accelerometer) to measure the user’s position and direction. A navigation and way-finding system [34
] for visually-impaired persons used RFID technology to estimate the position of the user. The system was designed for indoor use, and tags were installed under the floor. The tag reader was attached to a shoe or a stick that sent a query to tags. The orientation guiding system built by Ghiani et al. [35
] for blind persons actually used vibrotactile feedback. The prototype used the RFID network and tags to determine the person’s surroundings, and was installed inside the museum to guide blind persons. Similarly, Colace et al. [36
] developed a context-aware application based on a slow intelligence approach for cultural heritage application. The developed system was implemented as an application for the Android System. A case study with 50 users was conducted in which the users were made to visit in some rooms of the Capodimonte museum (Salerno, Italy ). The results showed that the users were satisfied with the performance of the application. Another RFID-based system [37
] helped blind users to identify objects in the home/classroom. The system had four major components: RFID Reader, FM Transmitter, Database Server, and RFID Tags. The system developed by El-Alamy et al. [38
] allowed visually-impaired persons to catch buses safely. The framework incorporated an auditory device, a tactile interface, and a wireless communication system. It also included a sensor, a radio frequency reader (RF) that was employed in the transport station. A wearable device was designed by Jain [39
] to aid blind persons in indoor navigation. The system had two major constituents: wall modules were installed in the building, and the user end included a waist-worn gadget linked to a smartphone. All instructions were communicated to the user via the Text-to-Speech (TTS) engine of the smartphone application. The “Drishti” project [40
] was aimed at designing a standalone-integrated system to help blind and low-vision individuals during outdoor navigation. It consisted of a wearable computer, GPS receiver, headset, and access to a wireless network for position information and way-guidance in the form of text-to-speech (TTS) voice commands. Gomez et al. [41
] also developed a system to provide visually-impaired persons with a more practical and functional device based on the sensory substitution methods (SSDs). The device was called the See ColOr, and consisted of SSD, a 3D camera, bone-phones, an iPad for tactile feedback, and a 14-inch laptop. The recognition module based on computer vision allowed the users to reach targets and avoid obstacles. Similarly, Iannizzotto et al. [42
] developed a system to help blind people to discover objects in the indoor environment around them. The system read the barcode attached to all interested objects. This system used an ultrasonic sensor to detect obstacles (i.e., objects with no tags). The ultrasonic system was attached to the user’s belt. This system used a head-mounted camera to read barcode tags, and a headphone to get the voice feedback of the query about any interested object passed to the system. Ando et al. [43
] developed a device based on an IR multisensory array that could help blind people in environment orientation and movement. It was based on smart signal processing to provide the user with suitable information about the position of obstacles found in his/her path.
The emergence and evolution of the concept and technologies of Ambient Intelligent (AmI) and ubiquitous computing have paved the way towards building smart environments. These smart environments exploit the key enabling technologies, which are necessary to improve the quality of life and performance and provide assistance in different kinds of environments. AmI has specific features, attributes, and aspects, including context-awareness. A context-aware system provides a predictive behavior based on knowledge of the environment. A few researchers, including Cooper and Cooper [44
], have addressed the issue of quality of life for people who suffered spinal cord injuries. They stated that technology plays a critical role in promoting the well-being, activity, and participation of individuals with spinal cord injury (SCI). School, work, travel, and leisure activities can all be facilitated by the technology. They pointed out that software has made computer interfaces adaptive and intelligent, through learning of the user’s behavior and optimizing its structure. Another important concept that can be employed in an assistive workplace for PWDs is the “Internet of Things (IoT)” [45
]. The IoT can offer PWDs the assistance and support, they need to achieve a good quality of life and allows them to participate in social and economic life. The IoT depicts a world of networked smart devices, where everything is interconnected and has a digital entity [46
]. According to Giannetsos et al. [47
], user-based technologies can never succeed without appropriate provisions addressing security and privacy. As a result of the ubiquitous nature of data emerging from the sensors carried by people, the highly dynamic and mobile setting presents new challenges for information security, data privacy, and ethics. To overcome security issues in IoT m-Health devices, Doukas et al. [48
] employed a system based on digital certificates and Public Key Infrastructure (PKI) data encryption. An adaptive approach, as proposed by Yau et al. [49
], can also be used to prevent communication systems from various security attacks. Similarly, Templeton [50
] addressed the issues of the security challenges in the increased use of cyber-physical devices in assistive environments. In fact, there have been many instances where the AT system was not properly secure, which means they were susceptible to fraud and harm as a result of unexpected interaction with other systems.
Most of the research works presented in this section have focused on home or outdoor ATs and neglected the social inclusion of PWDs in universities. In addition, most of the developed smart solutions and ATs were not comprehensive, as they addressed only one or two impairments. Furthermore, few of these papers attempted to analyze the behavior of PWD and provide relevant intervention methods to guide them at home or in the workplace.
Furthermore, it is clear from this section that the use of technologies based on GIS and LBS in mobile applications can help PWDs and other students on the university campus. This would also help in monitoring user activities and help PWDs in accessing and sharing of information flexibly. However, there have been issues, such as network security, interactive application and social networks and the use of IoT, etc., that require further attention. Moreover, a smart context-aware based design would help in analyzing PWDs users’ needs and to perform their activities efficiently. It also goes beyond meeting the users’ requirements by designing and implementing a smart AT solution that is adaptable to different conditions according to the specific context, which helps to attain better user satisfaction and adoption. A USCAS-PWD would assist PWDs in accessing relevant information anywhere on the campus freely, flexibly, securely, and at all times. It would also help them to communicate with each other and their caregivers efficiently and effectively. The design of such system on the university campus and within the buildings would require the identification of the user (PWDs) needs through a proper framework and design methodology. This methodology should be able to assess their needs and match them to relevant technologies that can satisfy them, as described in next section. Moreover, in order to support behavior analysis and intervention, there is a need of a wireless network that can be used to track user movements within the building. Real time tracking location system (RTLS) can be useful for behavior analysis of PWDs, as it helps to identify their location within the home, building, and work environments. The RFID and sensor networks play an essential role in tracking assets within a defined environment, where it transmits the identity associated with these assets wirelessly using radio waves [51
5. Discussion and Conclusions
A universal interface that supports AT solution has been designed by following the ATA and HAAT design methodologies to satisfy the needs of PWDs. The proposed solution is based on a Smart and Context-Aware at University Campus for PWDs. The USCAS-PWD represents a smart solution that is universal, adaptive, mobility supportive, flexible, and provides an effective comprehensive solution, including search for implementing a professional networking tool, which can be used by the researchers and students and PWDs with different impairment conditions. This application interface supports PWDs on the university campus and inside a building that is equipped with a RFID–WiFi network. The USCAS-PWD program uses asp.net programming languages along with SQL database for the campus network, and RFID–WiFi technology indoors to determine the user’s location. The user location-based search, along with the adaptive user profile and keyword-search, together make the GIS solution—smart and very effective in determining the relevant information for parties as well as providing the ability to communicate with others effectively. The implementation presented in this paper proves a successful smart flexible search and professional networking tool that makes the working environment for students—including PWDs—more productive. The Smart Help feature facilitates the usage of a system for PWD that works on their voice commands by voice recognition system. Furthermore, an intervention event and behavior-based algorithm, as well as a direction movement algorithm have been devised, which help in identifying the behavior of PWD students and taking the right actions to inform caregivers about any issues so that they can be aware of PWD critical activities. This tracking of behavior assists PWDs by alerting them or their caregiver about future or missing events. Moreover, the global acceptance and the cultural aspects of this type of technology can be realized from the positive feedback received from the users. The feedback that has been received actually reflects the global acceptance of the proposed technologies.
The proposed universal interface based on USCAS solution to support multiple PWD users on the university campus proved to be successful in meeting their needs while moving indoors, sitting in the class rooms, and moving outdoors on the university campus. This is done through smart help and communication solutions as well as smart tools that are context-aware and help PWD users and students to do their task effectively. However, some of the issues related to conducting extensive user studies to evaluate the diverse environment and conducting relevant usability studies need to be done, so that a better solution can be achieved. Furthermore, addressing the privacy issues of PWDs needs to be improved in the future in order to accommodate all impairment conditions and cultural diversity. Future research should incorporate PWD students’ needs at the university level to address the curriculum for different departments, to integrate the student registration interface, and to allow PWD students to access their related course materials and interact with them online. Moreover, the AT smart interface should support student forums to address their needs so that feedback can be collected from these forums to improve the design interface continuously.
For future endeavors, the authors would evaluate the interconnectivity of the proposed system with other technologies, such as cars, bikes, etc. They will also consider implementing the solution to run on different mobile platforms, such as Android and Windows.