To facilitate connectivity to the internet, the easiest way to establish communication infrastructure in areas affected by natural disaster and in remote locations with intermittent cellular services and/or lack of Wi-Fi coverage is to deploy an end-to-end connection over Mobile Ad-hoc Networks (MANETs). However, the potentials of MANETs are yet to be fully realized as existing MANETs routing protocols still suffer some major technical drawback in the areas of mobility, link quality, and battery constraint of mobile nodes between the overlay connections. To address these problems, a routing scheme named Mobility, Residual energy and Link quality Aware Multipath (MRLAM) is proposed for routing in MANETs. The proposed scheme makes routing decisions by determining the optimal route with energy efficient nodes to maintain the stability, reliability, and lifetime of the network over a sustained period of time. The MRLAM scheme uses a Q-Learning algorithm for the selection of optimal intermediate nodes based on the available status of energy level, mobility, and link quality parameters, and then provides positive and negative reward values accordingly. The proposed routing scheme reduces energy cost by 33% and 23%, end to end delay by 15% and 10%, packet loss ratio by 30.76% and 24.59%, and convergence time by 16.49% and 11.34% approximately, compared with other well-known routing schemes such as Multipath Optimized Link State Routing protocol (MP-OLSR) and MP-OLSRv2, respectively. Overall, the acquired results indicate that the proposed MRLAM routing scheme significantly improves the overall performance of the network.

As the enterprise of the “Internet of Things” is rapidly gaining widespread acceptance, sensors are being deployed in an unrestrained manner around the world to make efficient use of this new technological evolution. A recent survey has shown that sensor deployments over the past decade have increased significantly and has predicted an upsurge in the future growth rate. In health-care services, for instance, sensors are used as a key technology to enable Internet of Things oriented health-care monitoring systems. In this paper, we have proposed a two-stage fundamental approach to facilitate the implementation of such a system. In the first stage, sensors promptly gather together the particle measurements of an android application. Then, in the second stage, the collected data are sent over a Femto-LTE network following a new scheduling technique. The proposed scheduling strategy is used to send the data according to the application’s priority. The efficiency of the proposed technique is demonstrated by comparing it with that of well-known algorithms, namely, proportional fairness and exponential proportional fairness.

An evaluation of a force feedback joystick for a powered wheelchair is performed. Our aim is to deter- mine if the force feedback joystick enhances the driving per - formance of persons with severe disabilities. A Microsoft R ° Sidewinder TM Force Feedback joystick 2 is used with a com- puter simulation system for the evaluation phase of the stud y. The factor used to determine the feedback force of the joy- stick is the displacement vectors of sixteen sensors to the nearest obstacles. The preliminary results on persons with - out disability show that there are fewer collisions when the force feedback algorithm is activated compared to their per - formance when the algorithm is not activated. All test sub- jects agreed that when the force feedback algorithm is ac- tivated, the wheelchair guidance is easier in corridor dis- placement. Moreover, some subjects found it easier for door crossing.

Purpose: The study examines the remote integration process of advanced manufacturing technology (AMT) into the production system and identifies key challenges and mitigating actions for a smoother introduction and integration process.Design/methodology/approach: The study adopts a case study approach to a cyber-physical production system at an industrial technology center using a mobile robot as an AMT.Findings: By applying the plug-and-produce concept, the study exemplifies an AMT's remote integration process into a cyber-physical production system in nine steps. Eleven key challenges and twelve mitigation actions for remote integration are described based on technology–organization–environment theory. Finally, a remote integration framework is proposed to facilitate AMT integration into production systems.Practical implications: The study presents results purely from a practical perspective, which could reduce dilemmas in early decision-making related to smart production. The proposed framework can improve flexibility and decrease the time needed to configure new AMTs in existing production systems.Originality/value: The area of remote integration for AMT has not been addressed in depth before. The consequences of lacking in-depth studies for remote integration imply that current implementation processes do not match the needs and the existing situation in the industry and often underestimate the complexity of considering both technological and organizational issues. The new integrated framework can already be deployed by industry professionals in their efforts to integrate new technologies with shorter time to volume and increased quality but also as a means for training employees in critical competencies required for remote integration.

This paper presents an algebraic method to design a dynamic gain unknown input observer for linear systems with commensurate delays in state, input and output variables. Necessary and sufficient conditions for the existence of such an observer are provided as well as a constructive procedure. An example is given in order to illustrate the proposed method.