Optimized Design of Mechanical Chain Drive Based on a Wireless Sensor Network Data Algorithm

In this paper, we use a wireless sensor network data algorithm to optimize the design of mechanical chain drive by conducting an in-depth study of the mechanical chain drive optimization. We utilize the crowdsourcing feature of the swarm-wise sensing network for assisted wireless sensor networking to achieve crowdsourcing-assisted localization. We consider a framework for crowdsourcing-assisted GPS localization of wireless sensor networks and propose two recruitment participant optimization objectives, namely, minimum participants and time efficiency, respectively. A model and theoretical basis are provided for the subsequent trusted data-driven participant selection problem in swarm-wise sensing networks. The sprocket-chain engagement frequency has the greatest influence on the horizontal bending-vertical bending composite in different terrain conditions. The dynamic characteristics under working conditions are most influenced, while the scraping of the scraper and the central groove significantly influenced horizontal bending and vertical bending. Under load conditions, the amplitude of the scraper and central groove scraping increases significantly, which harm the dynamics of the scraper conveyor. By monitoring the speed difference between the head and tail sprockets and the overhang of the scraper, the tensioning status of the scraper conveyor chain can be effectively monitored to avoid chain jamming and chain breakage caused by the loose chain, thus improving the reliability and stability of the scraper conveyor.

Stakeholders’ Views on Responsible Assessments of Assistive Technologies through an Ethical HTA Matrix

Assessments of novel assistive technologies for use in home-based services has been documented to be performed in a variety of ways and often with a rather narrow focus on safety and effect or effectiveness. In order better to understand the place for wider forms of assessments of assistive technologies, the current study presents a combination of the Ethical Matrix and the Socratic approach for assessment of health technologies—the Ethical HTA Matrix. This matrix was filled with content based on a case of a GPS localization system, which was validated by stakeholders. In a next step, central decision-makers in assistive technologies and stakeholders were interviewed concerning their views on this methodology. Mainly, the matrix was seen as very comprehensive, but too detailed with an abundance of information. Nevertheless, some informants suggested concrete uses of the matrix in their organizations. Some understood the matrix more as an epistemic tool aiming at providing an overview of the state of knowledge, while others identified a normative potential in the matrix that could be implemented in health innovation processes for the home-based services, in particular when discussing novel solutions and working methods with health professionals and care workers.

Performance Evaluation of Non-GPS Based Localization Techniques under Shadowing Effects

Non-GPS localization has gained much interest from researchers and industries recently because GPS might fail to meet the accuracy requirements in shadowing environments. The two most common range-based non-GPS localization methods, namely Received Signal Strength Indicator (RSSI) and Angle-of-Arrival (AOA), have been intensively mentioned in the literature over the last decade. However, an in-depth analysis of the weighted combination methods of AOA and RSSI in shadowing environments is still missing in the state-of-the-art. This paper proposes several weighted combinations of the two RSSI and AOA components in the form of pAOA + qRSSI, devises the mathematical model for analyzing shadowing effects, and evaluates these weighted combination localization methods from both accuracy and precision perspectives. Our simulations show that increasing the number of anchors does not necessarily improve the precision and accuracy, that the AOA component is less susceptible to shadowing than the RSSI one, and that increasing the weight of the AOA component and reducing that of the RSSI component help improve the accuracy and precision at high Signal-to-Noise Ratios (SNRs). This observation suggests that some power control algorithm could be used to increase automatically the transmitted power when the channel experiences large shadowing to maintain a high SNR, thus guaranteeing both accuracy and precision of the weighted combination localization techniques.

Cooperative obstacle avoidance for heterogeneous unmanned systems during search mission

The problem of cooperative obstacle avoidance by a group of unmanned ground vehicles (UGVs) and unmanned air vehicles (UAVs) during a typical search mission is addressed in this paper. The group of UAVs and UGVs are performing a search operation in the designated area. All the UAVs and UGVs are equipped with a vision sensor/LIDAR to identify the possible obstacles in the search space. Due to their operation on the ground, UGVs are more likely to encounter obstacles. The obstacle avoidance for UGV under the event of sensor failure is done with environment information from the nearest UAV. The UAV plans its trajectory according to the UGV’s expected future trajectory, leading towards the base station. The UGV replans its trajectory to avoid obstacles after obtaining the information from its nearest UAV. A simulation study is performed with 10 UAVs and five UGVs performing a search mission in 1[Formula: see text]km[Formula: see text][Formula: see text][Formula: see text]1[Formula: see text]km area. The proposed obstacle avoidance method is experimentally validated in the outdoor environment with an autonomous UAV equipped with a camera and an autonomous UGV navigating based on GPS localization and environment information from the UAV.