• Trade of pre-owned context-dependent-pricey mechanical equipment involves lots of uncertainty, due to the complexity of the condition checking procedure of this category of equipment. We put forward the idea of continuous operation monitoring and simple reporting to make this trade experience as efficient and peaceful as possible. To validate the practicality of the idea, we choose pre-owned passenger vehicles as the target use-case. In the last several years, the market for second-hand car sales has grown a lot, due to its affordability and rising new car prices, thus, giving it a larger share of the overall car market’s value. The used car trade is usually a time-consuming, stressful, and fraud-prone process. In this paper, we propose a system, which is a novel concept rather than technology, to represent the treatment history of a car simply with two scores, denoting the mechanical and the body treatments, using the electronic control unit and other add-on sensors’ information. These scores are cyclically and wirelessly transmitted to and recorded in a data center to be fetched at a later time. The two treatment scores alongside the production year, the mileage, the vehicle history reports, and online marketplace valuations provide buyers with comfort and peace of mind in choosing a used car.

Keywords: Used car, automotive, smart city, ECU, driving behavior

• Automatic License-Plate Recognition (ALPR) has widespread use in Intelligent Transportation Systems (ITS), security and surveillance systems, and crime investigation. However, the lack of a fixed setup and involvement of cameras with different qualities give rise to the generation of low-resolution (LR) images. Therefore, more recently introduced deep-learning resolution-upgrade algorithms are essential in modern ALPR systems. In this paper, we propose an additional selective Generative-Adversarial-Network (GAN) Super Resolution (SR) step between the two state-of-the-art You-Only-Look-Once (YOLO)v5-based License-Plate Detection (LPD) and Character Recognition (CR) steps. SR-GAN is proposed due to its perceptual information maintenance. Furthermore, selectiveness is suggested to avoid unnecessary high time-complexity impact. The experimental results show a significant accuracy increase of 18% and an average runtime of 86ms, suitable for many real-time applications.

Keywords: Deep Learning, Intelligent Transportation System, License-Plate Detection, Generative Adversarial Network, Super Resolution

• Purpose- Photovoltaic (PV) systems are experiencing exponential growth due to environmental concerns, unlimited and ubiquitous solar energy, and starting-to-make-sense panel costs.

Alongside designing more efficient solar panels, installing solar trackers and special circuitry for optimizing power delivery to the load according to a maximum power point tracking (MPPT) algorithm are other ways of increasing efficiency. However, it is critical for any efficiency increase to account for the power consumption of any amendments. Therefore, this paper proposes a novel tracker while employing MPPT to boost the PV system's actual efficiency accounting for the involved costs.

Design/methodology/approach- The proposition is an experimental pneumatic dual-axis solar tracker using light-dependent resistor (LDR) sensors. Due to its embedded energy storage, the pneumatic tracker offers a low duty-cycle operation leading to tracking energy conservation, fewer maintenance needs, and scalability potential. While MPPT assures maximum load power delivery, the solar PV's actual delivered power is calculated for the first time, accounting for the solar tracking and MPPT power costs.

Findings- The experiments' results show an increase of 37.6% in total and 35.3% in actual power production for the proposed solar tracking system compared to the fixed panel system, with an MPPT efficiency of 90%. Thus, the pneumatic tracking system offers low tracking-energy consumption and good actual power efficiency. Also, the newly proposed pneumatic stimulant can significantly simplify the tracking mechanism and benefit from several advantages that come along with it.

Originality/value- This work proposes, for the first time, a single-motor pneumatic dual-axis tracker with less implementation cost, less frequent operation switching, and scalability potential, to be developed in future works. Also, the pneumatic proposal delivers high actual power efficiency for the first time to be addressed.

Keywords: Photovoltaic, Solar tracker, Dual axis, Pneumatic actuator