The Internet of Things (IoT) is becoming pervasive and immersive due to the recent advancements in communication and sensing technologies. The proliferation of smart devices and their sensing capabilities has opened new opportunities and business models. The billions of connected sensing devices are generating enormous amount of data. The sensing as a service concept has the potential to provide a wide variety of services to citizens, companies and public administrations. This paper presents a sensing as service vision for IoT in different domains such as agriculture, waste management, supply chain, traffic management and others. Moreover, different applications of sensing as service model is analyzed and discussed in detail. In this paper, we specifically propose a service oriented sensing as service architecture to realize the vision of sensing as a service. The proposed service oriented architecture has the potential to address the challenges of heterogeneity, integration and interoperability of a sensing as service concept and can open new business opportunities.

Due to the enormous growth of social media the potential of social media mining has increased exponentially. Individual users are producing data at unprecedented rate by sharing and interacting through social media. This user generated data provides opportunities to explore what people think and express on social media. Users exhibit different behaviors on social media towards individuals, a group, a topic or an activity. In this paper, we present a social media mining approach to perform behavior analytics. In this research study, we performed a descriptive analysis of user generated data such as users’ status, comments and replies to identify individual users or groups which can be a potential threat. Tokenization technique is used to estimate the polarity of the behavior of different users by considering their comments or feedbacks against different posts on Facebook. The proposed approach can help to identify possible threats reflected by the user’s behavior towards a specific event. To evaluate the approach, a data set was developed containing comments on the Facebook from different users in different groups. The dataset was divided into different groups such as political, religious and sports. Most negative users’ in different groups were identified successfully. In our research, we focused only on English content; however, it can be evaluated with other languages.

The monitoring of road conditions and surface anomalies such as potholes, bumps etc., has shown a great importance in the safety and comfort of road users from pedestrian to drivers. Detection and identification of such road anomalies not only reduces the causes of road accidents but also avoid vehicle damages. This can provision the management authorities to keep a track of road conditions along with maintenance of roads. Monitoring the road conditions is a challenging task and potholes detection plays an important role in the repairing of asphalt road surface. Many approaches exist to collect data about road surface conditions, however most of these approaches are low-speed human visual inspection or approaches that uses advanced and costly measuring equipments. Therefore, there is a need to develop a cost effective system that can manages these kind of issues. In this paper, a Participatory Sensing system based on raspberry pi is designed and developed to detect and record road surface anomalies that are measured by the inertial measurement unit (IMU) and GPS sensor. An android application is also designed and developed to alert the user from an upcoming high-intensity rough area on the road. Message Queuing Telemetry Transport (MQTT) protocol is used to publish and subscribe data from raspberry pi to data servers.

Personalization has become an essential feature of mobile services of different domains. On the other hand, users have conflicting needs of personalized experience and privacy. This leads to the question of how to maximize the user’s experience of personalized mobile services while keeping privacy. One possible solution is to provide user’s control of their personal data by keeping their user model on their personal mobile devices. In this way, a user can scrutinize the data while sharing with service providers depending on her/his requirements. The client-side personalization approach can shift the control of privacy to the users and can involve them in personalization process. Transparency and user control can increase the user’s trust. In this paper, we have proposed a solution with the objective of scrutable client-side personalization while keeping the user in control of both privacy and personalization process.

Personalization is gaining more importance with the increase of mobile and community services. Provision of personalized mobile services can help to meet the individual needs at a time and place when and where a user needs it. Mobile services should be designed to be usable and useful to realize the benefits of personalization. It is not an easy task to satisfy the individual's goals or needs. Currently, mobile services are designed either using a client side or server- side approach. At the same time, it is raising different research issues ranging from technological to security or privacy concerns. In this work, we described the current research and development in the area of personalization of mobile services. The objective of this paper is to analyze which design approach is suitable for the personalization of mobile services. Finally, we have discussed issues and challenges related to client-side personalization vs server-side personalization and the recent trends in personalization of mobile services.