Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

A Multi Views Approach for Remote Sensing Fusion Based on Spectral, Spatial and Temporal Information

The objectives of this chapter are to contribute to the apprehension of image fusion approaches including concepts definition, techniques ethics and results assessment. It is structured in five sections. Following this introduction, a definition of image fusion provides involved fundamental concepts. Respectively, we explain cases in which image fusion might be useful. Most existing techniques and architectures are reviewed and classified in the third section. In fourth section, we focuses heavily on algorithms based on multi-views approach, we compares and analyses the process model and algorithms including advantages, limitations and applicability of each view. The last part of the chapter summarized the benefits and limitations of a multi-view approach image fusion; it gives some recommendations on the effectiveness and the performance of these methods. These recommendations, based on a comprehensive study and meaningful quantitative metrics, evaluate various proposed views by applying them to various environmental applications with different remotely sensed images coming from different sensors. In the concluding section, we fence the chapter with a summary and recommendations for future researches

Real-time sensor data development for smart truck drivetrains

Heavy articulated transport vehicles have a poor reputation associated with dramatic road accidents with frequent fatalities for those in automobiles. The result of this work is a formal data flow structure to enhance real-time decision-making in complex mechanical systems to increase performance capability and responsiveness to human commands. This structure recognizes the multiple layers of highly non-linear mechanical components (actuators, wheel tire & ground surfaces, controllers, power supplies, human/machine interfaces, etc.) that must operate in unison (i.e., reduce conflicts) in real-time (in milli-seconds) to enhance operator (driver) control to maximize human choice. This work contains a discussion on dependable sensor data is vital in complex systems that rely on a suite of sensors for both control as well as condition monitoring purposes as well as discussion on real-time energy distribution analysis in high momentum mechanical systems. The focus will be on tractor trucks of class 7 & 8 that are outfitted with an array of low-cost redundant sensors leveraging advances in intelligent robotic systems. This work details many topics including: Most relevant sensor types and their technologies, Designing, implementing, and maintaining a multi-sensor system using feasible industry standards, Sensor signal integrity and data flow processing for decision making, Asynchronous data flow methods for operating decision making schemes in real-time, Multiple applications to enhance tractor trucks systems with multi-sensor systems for real-time decision making.Mechanical Engineerin

A study of the application of adaptive optics (AO) in optical coherence tomography (OCT) and confocal microscopy for the purpose of high resolution imaging

A problem is presented when imaging the eye in that optical aberrations are introduced by tissues of the anterior eye such as the cornea and lens. Adaptive optics (AO) and scanning laser ophthalmoscopy (SLO) have been combined to detect and compensate for these aberrations through the use of one or more correcting devices. Di erent corrector options exist, such as a liquid crystal lens or a deformable mirror (DM), such as that used in this thesis. This study seeks to use the ability of the DM to add focus/defocus aberrations to the closed loop AO system. This procedure could allow for dynamic focus control during generation of B-scan images using spectral domain optical coherence tomography (SD-OCT), where typically this is only possible using slower time domain techniques. The confocal gate scanning is controlled using the focus altering aberrations created by changing the shape of the deformable mirror. Using the novel master-slave interferometry method, multiple live en-face images can be acquired simultaneously. In this thesis, application of this method to an AO system is presented whereby en-face images may be acquired at multiple depths simultaneously. As an extension to this research, an OCT despeckle method is demonstrated. Further to this work is the investigation of the role in AO for optimisation of optical systems without the requirement for direct aberration measurement. Towards this end, genetic algorithms (GA) may be employed to control the DM in an iterative process to improve the coupling of light into fibre

A Small Acoustic Goniometer for General Purpose Research

Understanding acoustic events and monitoring their occurrence is a useful aspect of many research projects. In particular, acoustic goniometry allows researchers to determine the source of an event based solely on the sound it produces. The vast majority of the acoustic goniometry research projects used custom hardware targeted to the specific application under test. Unfortunately, due to the wide range of sensing applications, a flexible general purpose hardware/firmware system does not exist for this research. This dissertation focuses on the development of such a system which encourages the continued exploration of general purpose hardware/firmware and lowers barriers to research in projects requiring the use of acoustic goniometry. Simulations have been employed to verify system feasibility, and a complete hardware implementation of the acoustic goniometer has been designed and field tested. The results are reported, and suggested areas for improvement and further exploration are discussed

Multisource Data Integration in Remote Sensing

Papers presented at the workshop on Multisource Data Integration in Remote Sensing are compiled. The full text of these papers is included. New instruments and new sensors are discussed that can provide us with a large variety of new views of the real world. This huge amount of data has to be combined and integrated in a (computer-) model of this world. Multiple sources may give complimentary views of the world - consistent observations from different (and independent) data sources support each other and increase their credibility, while contradictions may be caused by noise, errors during processing, or misinterpretations, and can be identified as such. As a consequence, integration results are very reliable and represent a valid source of information for any geographical information system