A Reduced Complexity of Vahedi's Tag Estimation Method for DFSA

In order to calculate the number of tags in a radio frequency identification (RFID) system, several tag estimation methods have been investigated in literature and most of the available estimation methods need the overall knowledge of idle, success and collision slots of the previous frame to carry out the tag estimation process. In this article, we present three techniques to reduce the complexity of Vahedi’s tag estimation for tag collision resolution in RFID systems using dynamic frame slotted ALOHA. Our modified and useful approach considers the information about only the number of empty, successful or colliding slots in the previous frame for the tag estimation. Three decision rules were obtained by maximizing the likelihood of success, idle and collision which helps in the reduction of complexity substantially. However, the accuracy of estimation decreases for success-only and idle-only methods while the collision-only method gives a consistent and lower estimate error when the frame sizes and the number of tags increase

Hardware Software Co-Design of a Farming Robot

Food means life and no one can think about living without food. This is the most fundamental human necessity and food security is one of the major global concern of this century. With the revolution and recent advancements in the field of electronics and communication, there has been a paradigm shift from conventional farming ways to the modern one. This paper talks about the development of hardware software co-design of agricultural farming robot. Our developed farming robot has two parts namely hardware part which further consists of mechanical, electrical, control and tools segments and the software part which allows user to interact with the farming robot via cloud service. Our proposed hardware architecture is compatible with commercial Farmbot product and the developed web-based software can be extended for more features and applications. Furthermore, the developed robot has been tested and it works well

Digital-Twins towards Cyber-Physical Systems: A Brief Survey

Cyber-Physical Systems (CPS) are integrations of computation and physical processes. Physical processes are monitored and controlled by embedded computers and networks, which frequently have feedback loops where physical processes affect computations and vice versa. To ease the analysis of a system, the costly physical plants can be replaced by the high-fidelity virtual models that provide a framework for Digital-Twins (DT). This paper aims to briefly review the state-of-the-art and recent developments in DT and CPS. Three main components in CPS, including communication, control, and computation, are reviewed. Besides, the main tools and methodologies required for implementing practical DT are discussed by following the main applications of DT in the fourth industrial revolution through aspects of smart manufacturing, sixth wireless generation (6G), health, production, energy, and so on. Finally, the main limitations and ideas for future remarks are talked about followed by a short guideline for real-world application of DT towards CPS

Simulation of Signal Coverage for Terahertz Communications

Recent progress in wireless communication technology has started to see proposals for spectrum operation in the Terahertz band (0.1 THz to 10 THz), which will lead to data rates close to Terabit per second (Tbps). However,there are a number of challenges with the signals operating in the THz band, and this includes the requirements of Line-of-sight, signal attenuation due to molecular absorption, as well as signal scattering upon reflection from rough surfaces. This paper addresses a software-defined reflector solution for mirror-assisted terahertz communications. The paper also discusses future outlook that further improve reflectos for terahertz communications

Simulation-Based Headway Optimization for the Bangkok Airport Railway System under Uncertainty

The ever-increasing demand for intercity travel, as well as competition among all modes of transportation, is an unavoidable reality that today’s urban rail transit system must deal with. To meet this problem, urban railway companies must try to make better use of their existing plans and resources. Analytical approaches or simulation modeling can be used to develop or change a rail schedule to reflect the appropriate passenger demand. However, in the case of complex railway networks with several interlocking zones, analytical methods frequently have drawbacks. The goal of this article is to create a new simulation-based optimization model for the Bangkok railway system that takes into account the real assumptions and requirements in the railway system, such as uncertainty. The common particle swarm optimization (PSO) technique is combined with the developed simulation model to optimize the headways for each period in each day. Two different objective functions are incorporated into the models to consider both customer satisfaction by reducing the average waiting time and railway management satisfaction by reducing needed energy usage (e.g., reducing operating trains). The results obtained using a real dataset from the Bangkok railway system demonstrate that the simulation-based optimization approach for robust train service timetable scheduling, which incorporates both passenger waiting times and the number of operating trains as equally important objectives, successfully achieved an average waiting time of 11.02 min (with a standard deviation of 1.65 min) across all time intervals