Together with an explosive growth of the mobile applications and emerging of cloud computing concept, mobile cloud computing (MCC) has been introduced to be a potential technology for mobile services. MCC integrates the cloud computing into the mobile environment and overcomes obstacles related to the performance (e.g., battery life, storage, and bandwidth), environment (e.g., heterogeneity, scalability, and availability), and security (e.g., reliability and privacy) discussed in mobile computing. This paper gives a survey of MCC, which helps general readers have an overview of the MCC including the definition, architecture, and applications. The issues, existing solutions, and approaches are presented. In addition, the future research directions of MCC are discussed. Copyright © 2011 John Wiley & Sons, Ltd.

A survey of mobile cloud computing: architecture, applications, and approaches

Providing accurate and opportune information on people's activities and behaviors is one of the most important tasks in pervasive computing. Innumerable applications can be visualized, for instance, in medical, security, entertainment, and tactical scenarios. Despite human activity recognition (HAR) being an active field for more than a decade, there are still key aspects that, if addressed, would constitute a significant turn in the way people interact with mobile devices. This paper surveys the state of the art in HAR based on wearable sensors. A general architecture is first presented along with a description of the main components of any HAR system. We also propose a two-level taxonomy in accordance to the learning approach (either supervised or semi-supervised) and the response time (either offline or online). Then, the principal issues and challenges are discussed, as well as the main solutions to each one of them. Twenty eight systems are qualitatively evaluated in terms of recognition performance, energy consumption, obtrusiveness, and flexibility, among others. Finally, we present some open problems and ideas that, due to their high relevance, should be addressed in future research.

A Survey on Human Activity Recognition using Wearable Sensors

http://wpage.unina.it/valerio.persico/pubs/CloudIoT_FGCS.pdf

Integration of Cloud computing and Internet of Things

The Object Management Group's (OMG) Model Driven Architecture (MDA) strategy envisages a world where models play a more direct role in software production, being amenable to manipulation and transformation by machine. Model Driven Engineering (MDE) is wider in scope than MDA. MDE combines process and analysis with architecture. This article sets out a framework for model driven engineering, which can be used as a point of reference for activity in this area. It proposes an organisation of the modelling 'space' and how to locate models in that space. It discusses different kinds of mappings between models. It explains why process and architecture are tightly connected. It discusses the importance and nature of tools. It identifies the need for defining families of languages and transformations, and for developing techniques for generating/configuring tools from such definitions. It concludes with a call to align metamodelling with formal language engineering techniques.

Model Driven Engineering

https://corescholar.libraries.wright.edu/cgi/viewcontent.cgi?article=1986&context=knoesis

Ontology paper: The SSN ontology of the W3C semantic sensor network incubator group

Research groups in both academia and industry have developed prototype systems to demonstrate the benefits of pervasive computing in various application domains. Unfortunately, many first-generation pervasive computing systems lack the ability to evolve as new technologies emerge or as an application domain matures. To address this limitation, the University of Florida's Mobile and Pervasive Computing Laboratory is developing programmable pervasive spaces in which a smart space exists as both a runtime environment and a software library. Service discovery and gateway protocols automatically integrate system components using generic middleware that maintains a service definition for each sensor and actuator in the space. The Gator Tech Smart House in Gainesville, Florida, is the culmination of more than five years of research in pervasive and mobile computing. The project's goal is to create assistive environments such as homes that can sense themselves and their residents and enact mappings between the physical world and remote monitoring and intervention services.

The Gator Tech Smart House: a programmable pervasive space

In principle, activity recognition can be exploited to great societal benefits, especially in real-life, human centric applications such as elder care and healthcare. This article focused on recognizing simple human activities. Recognizing complex activities remains a challenging and active area of research and the nature of human activities poses different challenges. Human activity understanding encompasses activity recognition and activity pattern discovery. The first focuses on accurate detection of human activities based on a predefined activity model. An activity pattern discovery researcher builds a pervasive system first and then analyzes the sensor data to discover activity patterns.

/pdf/human-activity-recognition-and-pattern-discovery-12eo7ae22p.pdf

Human Activity Recognition and Pattern Discovery

The proliferation of mobile devices and the pervasiveness of wireless technology have provided a major impetus to replicate the network-based service discovery technologies in wireless and mobile networks. However, existing service discovery protocols and delivery mechanisms fall short of accommodating the complexities of the ad-hoc environment. They also place emphasis on device capabilities as services rather than device independent software services, making them unsuitable for m-commerce oriented scenarios. Konark is a service discovery and delivery protocol designed specifically for ad-hoc, peer-to-peer networks, and targeted towards device independent services in particular. It has two major aspects - service discovery and service delivery. For discovery, Konark uses a completely distributed, peer-to-peer mechanism that provides each device the ability to advertise and discover services in the network. The approach towards service description is XML based. It includes a description template that allows services to be described in a human and software understandable forms. A micro-HTTP server present on each device handles service delivery, which is based on SOAP. Konark provides a framework for connecting isolated services offered by proximal pervasive devices over a wireless medium.

Konark - a service discovery and delivery protocol for ad-hoc networks

There are many navigation systems for visually impaired people but few can provide dynamic interactions and adaptability to changes. None of these systems work seamlessly both indoors and outdoors. Drishti uses a precise position measurement system, a wireless connection, a wearable computer, and a vocal communication interface to guide blind users and help them travel in familiar and unfamiliar environments independently and safely. Outdoors, it uses DGPS as its location system to keep the user as close as possible to the central line of sidewalks of campus and downtown areas; it provides the user with an optimal route by means of its dynamic routing and rerouting ability. The user can switch the system from an outdoor to an indoor environment with a simple vocal command. An OEM ultrasound positioning system is used to provide precise indoor location measurements. Experiments show an in-door accuracy of 22 cm. The user can get vocal prompts to avoid possible obstacles and step-by-step walking guidance to move about in an indoor environment. This paper describes the Drishti system and focuses on the indoor navigation design and lessons learned in integrating the indoor with the outdoor system.

Drishti: an integrated indoor/outdoor blind navigation system and service

Gainesville, Florida, 10 March 2 012. Today, the Mobile Location- Based Services Summit hosted a panel entitled "What Was Wrong with First-Generation Location-Based Services?" The panel chair, Sumi Helal of the University of Florida, invited two world-class experts in LBS history and technology to discuss the topic: Paolo Bellavista of the University of Bologna and Axel Kupper of the University of Munich. The panel discussed the popularity of today's LBSs and analyzed their distinguishing aspects in comparison with first-generation LBSs. The panel was anything but controversial, with all panelists in total agreement on what initially went wrong and why today's LBSs work. They analyzed how the failure unfolded to set the stage for a major paradigm shift in LBS business and technology and noted the milestones that shaped today's LBSs.

Sumi Helal

Papers

The Gator Tech Smart House: a programmable pervasive space

Human Activity Recognition and Pattern Discovery

Konark - a service discovery and delivery protocol for ad-hoc networks

Drishti: an integrated indoor/outdoor blind navigation system and service

Location-Based Services: Back to the Future