New strategic approaches for implementing intelligent streetscape towards livable streets in City of Riyadh

Streetscape can be considered as a term “which can be used to clarify and explain the street's built-in and the basic structure, also it is known as the design of the visual appeal and quality of the street effect. A good tool for improving urban quality and establishing a feeling of place is design of streetscape. People's requirements for public areas have changed as internet usage has continued to expand.. The numbers of people who use cars has increased a lot in Riyadh city. In reality, this leads to some problems in a direct and an indirect way, such as car accidents, traffic overcrowding, lack of services for bicyclists and pedestrians, weak social relationships between the people, and high obesity levels. Reconsider design of streetscape in Riyadh city especially in the era of digital information technology will revitalize regions by providing reshaping the urban experience toward higher livability that respond to and connect with onlookers in order to increase understanding of onlookers' activities in the streets, promote their sense of place, and improve safety and livability in urban areas.. The presented study focuses on the qualitative approach that is according to the related theoretical exploration and research; so, this paper combines the design of streetscape with digital information technology, with new ideas of intelligent streetscape’s design for enhancing Riyadh city to make the user's life livable. The current paper ended with proposed strategic approaches and suggestions to enhance the city of Riyadh's streetscape style as an outcome of the theoretical research. Results indicated that streets, which contain a close combination with the resident’s daily life activities and the important consequences on their mental comfort, have not attracted any care in terms of academic research. This resulted in a failure in providing solid strategic approaches for intelligent design of streetscape in Riyadh city

A comprehensive survey on hybrid communication in context of molecular communication and terahertz communication for body-centric nanonetworks

With the huge advancement of nanotechnology over the past years, the devices are shrinking into micro-scale, even nano-scale. Additionally, the Internet of nano-things (IoNTs) are generally regarded as the ultimate formation of the current sensor networks and the development of nanonetworks would be of great help to its fulfilment, which would be ubiquitous with numerous applications in all domains of life. However, the communication between the devices in such nanonetworks is still an open problem. Body-centric nanonetworks are believed to play an essential role in the practical application of IoNTs. BCNNs are also considered as domain specific like wireless sensor networks and always deployed on purpose to support a particular application. In these networks, electromagnetic and molecular communications are widely considered as two main promising paradigms and both follow their own development process. In this survey, the recent developments of these two paradigms are first illustrated in the aspects of applications, network structures, modulation techniques, coding techniques and security to then investigate the potential of hybrid communication paradigms. Meanwhile, the enabling technologies have been presented to apprehend the state-of-art with the discussion on the possibility of the hybrid technologies. Additionally, the inter-connectivity of electromagnetic and molecular body-centric nanonetworks is discussed. Afterwards, the related security issues of the proposed networks are discussed. Finally, the challenges and open research directions are presented

A Game-Theoretic Approach to Strategic Resource Allocation Mechanisms in Edge and Fog Computing

With the rapid growth of Internet of Things (IoT), cloud-centric application management raises questions related to quality of service for real-time applications. Fog and edge computing (FEC) provide a complement to the cloud by filling the gap between cloud and IoT. Resource management on multiple resources from distributed and administrative FEC nodes is a key challenge to ensure the quality of end-user’s experience. To improve resource utilisation and system performance, researchers have been proposed many fair allocation mechanisms for resource management. Dominant Resource Fairness (DRF), a resource allocation policy for multiple resource types, meets most of the required fair allocation characteristics. However, DRF is suitable for centralised resource allocation without considering the effects (or feedbacks) of large-scale distributed environments like multi-controller software defined networking (SDN). Nash bargaining from micro-economic theory or competitive equilibrium equal incomes (CEEI) are well suited to solving dynamic optimisation problems proposing to ‘proportionately’ share resources among distributed participants. Although CEEI’s decentralised policy guarantees load balancing for performance isolation, they are not faultproof for computation offloading. The thesis aims to propose a hybrid and fair allocation mechanism for rejuvenation of decentralised SDN controller deployment. We apply multi-agent reinforcement learning (MARL) with robustness against adversarial controllers to enable efficient priority scheduling for FEC. Motivated by software cybernetics and homeostasis, weighted DRF is generalised by applying the principles of feedback (positive or/and negative network effects) in reverse game theory (GT) to design hybrid scheduling schemes for joint multi-resource and multitask offloading/forwarding in FEC environments. In the first piece of study, monotonic scheduling for joint offloading at the federated edge is addressed by proposing truthful mechanism (algorithmic) to neutralise harmful negative and positive distributive bargain externalities respectively. The IP-DRF scheme is a MARL approach applying partition form game (PFG) to guarantee second-best Pareto optimality viii | P a g e (SBPO) in allocation of multi-resources from deterministic policy in both population and resource non-monotonicity settings. In the second study, we propose DFog-DRF scheme to address truthful fog scheduling with bottleneck fairness in fault-probable wireless hierarchical networks by applying constrained coalition formation (CCF) games to implement MARL. The multi-objective optimisation problem for fog throughput maximisation is solved via a constraint dimensionality reduction methodology using fairness constraints for efficient gateway and low-level controller’s placement. For evaluation, we develop an agent-based framework to implement fair allocation policies in distributed data centre environments. In empirical results, the deterministic policy of IP-DRF scheme provides SBPO and reduces the average execution and turnaround time by 19% and 11.52% as compared to the Nash bargaining or CEEI deterministic policy for 57,445 cloudlets in population non-monotonic settings. The processing cost of tasks shows significant improvement (6.89% and 9.03% for fixed and variable pricing) for the resource non-monotonic setting - using 38,000 cloudlets. The DFog-DRF scheme when benchmarked against asset fair (MIP) policy shows superior performance (less than 1% in time complexity) for up to 30 FEC nodes. Furthermore, empirical results using 210 mobiles and 420 applications prove the efficacy of our hybrid scheduling scheme for hierarchical clustering considering latency and network usage for throughput maximisation.Abubakar Tafawa Balewa University, Bauchi (Tetfund, Nigeria

A Real-Time Positioning System of Manufacturing Carriers Deploying Wireless MEMS Accelerometers and Gyroscopes

Modern manufacturing systems face ever-increasing pressure to maximize efficiency of production processes, minimize downtime due to unexpected deviations from normal operation, and maintain agility in dynamic market conditions. Detailed, real-time asset tracking is essential for achieving these goals. Pallets are widely-used for transporting raw materials, intermediate products, and final products in automated assembly and manufacturing lines. A sophisticated pallet monitoring system can provide possibilities for optimizing pallet routing in real time, enable dynamic scheduling changes, and historical traceability required for error diagnosis and repair. Traditionally, pallets are monitored by networks of sensors, such as RFID readers or proximity sensors to collect location data. These sensor networks are rarely dense enough to provide precise continuous data about pallet location. Real-time pallet tracking data is thus limited to recording timestamps at static checkpoints. This thesis presents an asset-aware management tool for continuous pallet location monitoring based on event logs obtained from intelligent wireless devices embedded in each pallet. Each wireless device, equipped with a 3-axis accelerometer and a 3-axis gyroscope, provides accurate information about pallet movement. The raw sensor data is pre-processed into an event stream, which is sent to a server over a 6LoWPAN network. The software developed in this research implements an algorithm for processing event logs to determine exact pallet location using artificial intelligence techniques. Calculated pallet position can be provided to high-level enterprise systems, and to manufacturing execution systems for use in scheduling, routing, and visualization of the production line. Designing the SCADA system was also part of this thesis. The solution was successfully deployed in the FASTory, a 12-cell light assembly line in the Factory Automation Systems and Technologies Laboratory (FAST-lab.) at Tampere University of Technology, as part of eSONIA, a European Commission-cofunded research project on using service-enabled embedded devices for realizing an asset-aware, self-recovering plant. The proposed solution demonstrates a novel approach for continuous, real-time pallet location tracking based on wireless sensors

Ubiquitous Robotics System for Knowledge-based Auto-configuration System for Service Delivery within Smart Home Environments

The future smart home will be enhanced and driven by the recent advance of the Internet of Things (IoT), which advocates the integration of computational devices within an Internet architecture on a global scale [1, 2]. In the IoT paradigm, the smart home will be developed by interconnecting a plethora of smart objects both inside and outside the home environment [3-5]. The recent take-up of these connected devices within home environments is slowly and surely transforming traditional home living environments. Such connected and integrated home environments lead to the concept of the smart home, which has attracted significant research efforts to enhance the functionality of home environments with a wide range of novel services. The wide availability of services and devices within contemporary smart home environments make their management a challenging and rewarding task. The trend whereby the development of smart home services is decoupled from that of smart home devices increases the complexity of this task. As such, it is desirable that smart home services are developed and deployed independently, rather than pre-bundled with specific devices, although it must be recognised that this is not always practical. Moreover, systems need to facilitate the deployment process and cope with any changes in the target environment after deployment. Maintaining complex smart home systems throughout their lifecycle entails considerable resources and effort. These challenges have stimulated the need for dynamic auto-configurable services amongst such distributed systems. Although significant research has been directed towards achieving auto-configuration, none of the existing solutions is sufficient to achieve auto-configuration within smart home environments. All such solutions are considered incomplete, as they lack the ability to meet all smart home requirements efficiently. These requirements include the ability to adapt flexibly to new and dynamic home environments without direct user intervention. Fulfilling these requirements would enhance the performance of smart home systems and help to address cost-effectiveness, considering the financial implications of the manual configuration of smart home environments. Current configuration approaches fail to meet one or more of the requirements of smart homes. If one of these approaches meets the flexibility criterion, the configuration is either not executed online without affecting the system or requires direct user intervention. In other words, there is no adequate solution to allow smart home systems to adapt dynamically to changing circumstances, hence to enable the correct interconnections among its components without direct user intervention and the interruption of the whole system. Therefore, it is necessary to develop an efficient, adaptive, agile and flexible system that adapts dynamically to each new requirement of the smart home environment. This research aims to devise methods to automate the activities associated with customised service delivery for dynamic home environments by exploiting recent advances in the field of ubiquitous robotics and Semantic Web technologies. It introduces a novel approach called the Knowledge-based Auto-configuration Software Robot (Sobot) for Smart Home Environments, which utilises the Sobot to achieve auto-configuration of the system. The research work was conducted under the Distributed Integrated Care Services and Systems (iCARE) project, which was designed to accomplish and deliver integrated distributed ecosystems with a homecare focus. The auto-configuration Sobot which is the focus of this thesis is a key component of the iCARE project. It will become one of the key enabling technologies for generic smart home environments. It has a profound impact on designing and implementing a high quality system. Its main role is to generate a feasible configuration that meets the given requirements using the knowledgebase of the smart home environment as a core component. The knowledgebase plays a pivotal role in helping the Sobot to automatically select the most appropriate resources in a given context-aware system via semantic searching and matching. Ontology as a technique of knowledgebase representation generally helps to design and develop a specific domain. It is also a key technology for the Semantic Web, which enables a common understanding amongst software agents and people, clarifies the domain assumptions and facilitates the reuse and analysis of its knowledge. The main advantages of the Sobot over traditional applications is its awareness of the changing digital and physical environments and its ability to interpret these changes, extract the relevant contextual data and merge any new information or knowledge. The Sobot is capable of creating new or alternative feasible configurations to meet the system’s goal by utilising inferred facts based on the smart home ontological model, so that the system can adapt to the changed environment. Furthermore, the Sobot has the capability to execute the generated reconfiguration plan without interrupting the running of the system. A proof-of-concept testbed has been designed and implemented. The case studies carried out have shown the potential of the proposed approach to achieve flexible and reliable auto-configuration of the smart home system, with promising directions for future research

Low-power Wearable Healthcare Sensors

Advances in technology have produced a range of on-body sensors and smartwatches that can be used to monitor a wearer’s health with the objective to keep the user healthy. However, the real potential of such devices not only lies in monitoring but also in interactive communication with expert-system-based cloud services to offer personalized and real-time healthcare advice that will enable the user to manage their health and, over time, to reduce expensive hospital admissions. To meet this goal, the research challenges for the next generation of wearable healthcare devices include the need to offer a wide range of sensing, computing, communication, and human–computer interaction methods, all within a tiny device with limited resources and electrical power. This Special Issue presents a collection of six papers on a wide range of research developments that highlight the specific challenges in creating the next generation of low-power wearable healthcare sensors

Cyber physical approach and framework for micro devices assembly

The emergence of Cyber Physical Systems (CPS) and Internet-of-Things (IoT) based principles and technologies holds the potential to facilitate global collaboration in various fields of engineering. Micro Devices Assembly (MDA) is an emerging domain involving the assembly of micron sized objects and devices. In this dissertation, the focus of the research is the design of a Cyber Physical approach for the assembly of micro devices. A collaborative framework comprising of cyber and physical components linked using the Internet has been developed to accomplish a targeted set of MDA life cycle activities which include assembly planning, path planning, Virtual Reality (VR) based assembly analysis, command generation and physical assembly. Genetic algorithm and modified insertion algorithm based methods have been proposed to support assembly planning activities. Advanced VR based environments have been designed to support assembly analysis where plans can be proposed, compared and validated. The potential of next generation Global Environment for Network Innovation (GENI) networking technologies has also been explored to support distributed collaborations involving VR-based environments. The feasibility of the cyber physical approach has been demonstrated by implementing the cyber physical components which collaborate to assemble micro designs. The case studies conducted underscore the ability of the developed Cyber Physical approach and framework to support distributed collaborative activities for MDA process contexts