Opportunistic data dissemination in mobile phone sensor networks

Situated communication technologies in emergencies are subject to decay or fail because of their inadequate services. With the advances in tiny-sensor technologies and ubiquity of smart phones, public awareness on urgent situations can be raised in more efficient and distributed ways. We center on opportunistic data dissemination schemes where the objective is to provide an operability among sensing, communication, and data spread. Such mobile networks do not require end-to-end routes or servers; however connectivity and scalability issues may last forever without determinism. We have started implementing context-aware services to understand the mobile phone carriers’ characteristics and routines in order to increase the quality of service in our collaboration and dissemination objectives. We are currently working on real implementation of mobile ad hoc networks and routing algorithms. Besides, we simulate an urban city network with different scenarios and objectives to analyze the open research challenges

Remote Control and Monitoring of Smart Home Facilities via Smartphone with Wi-Fly

Due to the widespread ownership of smartphone devices, the application of mobile technologies to enhance the monitoring and control of smart home facilities has attracted much academic attention. This study indicates that tools already in the possession of the end user can be a significant part of the specific context-aware system in the smart home. The behaviour of the system in the context of existing systems will reflect the intention of the client. This model system offers a diverse architectural concept for Wireless Sensor Actuator Mobile Computing in a Smart Home (WiSAMCinSH) and consists of sensors and actuators in various communication channels, with different capacities, paradigms, costs and degree of communication reliability. This paper focuses on the utilization of end users’ smartphone applications to control home devices, and to enable monitoring of the context-aware environment in the smart home to fulfil the needs of the ageing population. It investigates the application of an iPhone to supervise smart home monitoring and control electrical devices, and through this approach, after initial setup of the mobile application, a user can control devices in the smart home from different locations and over various distances

A survey on context awareness in big data analytics for business applications

The concept of context awareness has been in existence since the 1990s. Though initially applied exclusively in computer science, over time it has increasingly been adopted by many different application domains such as business, health and military. Contexts change continuously because of objective reasons, such as economic situation, political matter and social issues. The adoption of big data analytics by businesses is facilitating such change at an even faster rate in much complicated ways. The potential benefits of embedding contextual information into an application are already evidenced by the improved outcomes of the existing context-aware methods in those applications. Since big data is growing very rapidly, context awareness in big data analytics has become more important and timely because of its proven efficiency in big data understanding and preparation, contributing to extracting the more and accurate value of big data. Many surveys have been published on context-based methods such as context modelling and reasoning, workflow adaptations, computational intelligence techniques and mobile ubiquitous systems. However, to our knowledge, no survey of context-aware methods on big data analytics for business applications supported by enterprise level software has been published to date. To bridge this research gap, in this paper first, we present a definition of context, its modelling and evaluation techniques, and highlight the importance of contextual information for big data analytics. Second, the works in three key business application areas that are context-aware and/or exploit big data analytics have been thoroughly reviewed. Finally, the paper concludes by highlighting a number of contemporary research challenges, including issues concerning modelling, managing and applying business contexts to big data analytics. © 2020, Springer-Verlag London Ltd., part of Springer Nature

Towards a Context-Aware Knowledge Model for Smart Service Systems

The advancement of the Internet of things, big data, and mobile computing leads to the need for smart services that enable the context awareness and the adaptability to their changing contexts. Today, designing a smart service system is a complex task due to the lack of an adequate model support in awareness and pervasive environment. In this paper, we present a context-aware knowledge model for smart service systems that organizes the domain and context-aware knowledge into knowledge components based on the three levels of services: Services, Service system and Network of service systems. The context-aware knowledge model for smart service systems integrates all the information and knowledge related to smart services, knowledge components and context awareness that can play a key role for any framework, infrastructure, or applications deploying smart services. To demonstrate the approach, a case study about a chatbot as a smart service for customer support is presented

Distributed Hybrid Simulation of the Internet of Things and Smart Territories

This paper deals with the use of hybrid simulation to build and compose heterogeneous simulation scenarios that can be proficiently exploited to model and represent the Internet of Things (IoT). Hybrid simulation is a methodology that combines multiple modalities of modeling/simulation. Complex scenarios are decomposed into simpler ones, each one being simulated through a specific simulation strategy. All these simulation building blocks are then synchronized and coordinated. This simulation methodology is an ideal one to represent IoT setups, which are usually very demanding, due to the heterogeneity of possible scenarios arising from the massive deployment of an enormous amount of sensors and devices. We present a use case concerned with the distributed simulation of smart territories, a novel view of decentralized geographical spaces that, thanks to the use of IoT, builds ICT services to manage resources in a way that is sustainable and not harmful to the environment. Three different simulation models are combined together, namely, an adaptive agent-based parallel and distributed simulator, an OMNeT++ based discrete event simulator and a script-language simulator based on MATLAB. Results from a performance analysis confirm the viability of using hybrid simulation to model complex IoT scenarios.Comment: arXiv admin note: substantial text overlap with arXiv:1605.0487

Leveraging Application Development for the Internet of Mobile Things

So far, most of research and development for the Internet of Things has been focused at systems where the smart objects, WPAN beacons, sensors, and actuators are mainly stationary and associated with a fixed location (such as appliances in a home or office, an energy meter for a building), and are not capable of handling unrestricted/arbitrary forms of mobility. However, our current lifestyle and economy are increasingly mobile, as people, vehicles, and goods move independently in public and private areas (e.g., automated logistics, retail). Therefore, we are witnessing an increasing need to support Machine to Machine (M2M) communication, data collection, and processing and actuation control for mobile smart things, establishing what is called the Internet of Mobile Things (IoMT). Examples of mobile smart things that fit in the definition of IoMT include Unmanned Aerial Vehicles (UAVs), all sorts of human-crewed vehicles (e.g., cars, buses), and even people with wearable devices such as smart watches or fitness and health monitoring devices. Among these mobile IoT applications, there are several that only require occasional data probes from a mobile sensor, or need to control a smart device only in some specific conditions, or context, such as only when any user is in the ambient. While IoT systems still lack some general programming concepts and abstractions, this is even more so for IoMT. This paper discusses the definition and implementation of suitable programming concepts for mobile smart things - given several examples and scenarios of mobility-specific sensoring and actuation control, both regarding smart things individually, or in terms of collective smart things behaviors. We then show a proposal of programming constructs and language, and show how we will implement an IoMT application programming model, namely OBSACT, on the top of our current middleware ContextNet