The rapid development of urban cities coupled with the rise in population has led to an exponentially growing number of vehicles on the roads for the latter to commute. This is adding to the already overbearing problem of traffic congestion. Short term, costly and short-sighted solutions of road infrastructure expansions are no longer suitable. One effective method of road resource allocation is focusing on the widely used traffic signal controllers’ timing schedules. Searching for a suitable or an optimal schedule for the prior via brute force to ease traffic congestion might not be the most elegant or feasible solution. Nature-inspired algorithms including evolutionary and swarm intelligence algorithms are gaining a lot of momentum. Many of these algorithms have been used in the last two decades to address different applications in the smart city era including traffic signal control (TSC). This paper conducts a comprehensive literature review on applications of evolutionary and swarm intelligence algorithms to TSC. Surveyed work is categorized based on the set of decision variables, optimization objective(s), problem modeling and solution encoding. The paper, based on gaps identified by the conducted review, identifies promising future research directions and discusses where the future research is headed.

In this paper, the subject of embedded systems education in the Arduino age is examined. Arduino is an open-source microcontroller platform that has been widely popular in the past decade among hobbyists and academics. Arduino is increasingly being adopted in courses that span different disciplines in schools and universities. As a result, numerous papers are being published every year in different engineering education conferences and journals reporting the integration of Arduino in teaching. In this work, the impact of Arduino on embedded systems education is investigated. First, challenges facing embedded systems education are identified from the literature. Second, different Arduino teaching integration methodologies reported in the literature are surveyed and analyzed. Third, the question whether Arduino successfully addresses embedded education challenges or not is discussed taking both surveyed findings and recent market trends into consideration. Finally, a number of open-ended research directions are proposed.

This paper presents a comparative study between four techniques recently used to improve the wind energy conversion system (WECS) to water pumping systems. The WECS is a renewable energy source which has developed rapidly in recent years. The use of the WECS in the water pumping field is a free solution (economically) compared to the use of the electricity grid supply. The control of WECS, equipped with a permanent magnet synchronous generator, has the objective of carefully maximising power generation. A comparative study between the proposed Fuzzy Logic Control, optimised using a genetic algorithm and particle swarm optimisation algorithm, and the conventional Perturb and Observe MPPT method using Matlab/Simulink, is presented. The performance of the proposed system has been verified against the generated output voltage, current and power waveforms, intermediate circuit voltage waveform, and generator speed. The presented results demonstrate the effectiveness of the control strategy applied in this work.