Development and testing of braking and acceleration features for vehicle advanced driver assistance system

<span lang="EN-US">Traffic congestion is a constant problem for cities worldwide. The human driving inefficiency and poor urban planning and development contribute to traffic buildup and travel discomfort. An example of human inefficiency is the phantom traffic jam, which is caused by unnecessary braking, causing traffic to slow down, and eventually coming to a stop. In this study, a brake and acceleration feature (BAF) for the advanced driver assistance system (ADAS) is proposed to mitigate the effects of the phantom traffic phenomenon. In its initial stage, the BAF provides a heads-up display that gives information on how much braking and acceleration input is needed to maintain smooth driving conditions, i.e., without sudden acceleration or deceleration, while observing a safe distance from the vehicle in front. BAF employs a fuzzy logic controller that takes distance information from a light detection and ranging (LIDAR) sensor and the vehicle’s instantaneous speed from the engine control unit (ECU). It then calculates the corresponding percentage value of needed acceleration and braking in order to maintain travel objectives of smooth and safe-distance travel. Empirical results show that the system suggests acceleration and braking values slightly higher than the driver’s actual inputs and can achieve 90% accuracy overall.</span>

Quality of life among caregivers of thalassaemic children, attending at Thalassaemia control unit of a rural tertiary care hospital, in a sub-Himalayan district of West Bengal

Thalassaemia is a disease of abnormal development of red blood cells which manifests as anaemia. This chronic disease may cause mental, social, financial burdens on the families, care givers and also on health care system.To assess the quality of life (QOL) of the caregivers of thalassaemic children and to identify the predictors of quality of their physical and mental health.Institution based descriptive cross-sectional study conducted in the Thalassaemia Control Unit (TCU) of North Bengal Medical College (NBMC) from December 2018 to April 2019. Total 136 caregivers of children (≤12 years) with thalassaemia were included by complete enumeration method. Physical and mental health of the caregivers were reported in Short Form-36 (SF-36) Health Survey. Collected data were entered into MS-Excel, analysed with the help of SPSS (Version 22).Mean age of caregivers was 34.3 (SD ± 1.4 years). Most of caregivers were female (89%) and had educational qualification up to Primary school (45.6%). Majority (70.6%) of the caregivers were the mothers of the children. Most of the study participants (60.3%) had favourable Physical health Component Summary (PCS) but 64.7% of the caregivers had unfavourable Mental health component Summary (MCS). Educational status was found to be the predictor for PCS but age and relationship with the child were the predictors for MCS.Counselling, psychotherapy, social support for family members or caregivers of the thalassaemic children and community involvement with their full participation should be emphasized to reduce stigma related to thalassaemia.

Towards a Lightweight Intrusion Detection Framework for In-Vehicle Networks

With the emergence of networked devices, from the Internet of Things (IoT) nodes and cellular phones to vehicles connected to the Internet, there has been an ever-growing expansion of attack surfaces in the Internet of Vehicles (IoV). In the past decade, there has been a rapid growth in the automotive industry as network-enabled and electronic devices are now integral parts of vehicular ecosystems. These include the development of automobile technologies, namely, Connected and Autonomous Vehicles (CAV) and electric vehicles. Attacks on IoV may lead to malfunctioning of Electronic Control Unit (ECU), brakes, control steering issues, and door lock issues that can be fatal in CAV. To mitigate these risks, there is need for a lightweight model to identify attacks on vehicular systems. In this article, an efficient model of an Intrusion Detection System (IDS) is developed to detect anomalies in the vehicular system. The dataset used in this study is an In-Vehicle Network (IVN) communication protocol, i.e., Control Area Network (CAN) dataset generated in a real-time environment. The model classifies different types of attacks on vehicles into reconnaissance, Denial of Service (DoS), and fuzzing attacks. Experimentation with performance metrics of accuracy, precision, recall, and F-1 score are compared across a variety of classification models. The results demonstrate that the proposed model outperforms other classification models.

A New Wearable System for Sensing Outdoor Environmental Conditions for Monitoring Hyper-Microclimate

The rapid urbanization process brings consequences to urban environments, such poor air quality and the urban heat island issues. Due to these effects, environmental monitoring is gaining attention with the aim of identifying local risks and improving cities’ liveability and resilience. However, these environments are very heterogeneous, and high-spatial-resolution data are needed to identify the intra-urban variations of physical parameters. Recently, wearable sensing techniques have been used to perform microscale monitoring, but they usually focus on one environmental physics domain. This paper presents a new wearable system developed to monitor key multidomain parameters related to the air quality, thermal, and visual domains, on a hyperlocal scale from a pedestrian’s perspective. The system consisted of a set of sensors connected to a control unit settled on a backpack and could be connected via Wi-Fi to any portable equipment. The device was prototyped to guarantee the easy sensors maintenance, and a user-friendly dashboard facilitated a real-time monitoring overview. Several tests were conducted to confirm the reliability of the sensors. The new device will allow comprehensive environmental monitoring and multidomain comfort investigations to be carried out, which can support urban planners to face the negative effects of urbanization and to crowd data sourcing in smart cities.

Removal of Pathogens from Domestic Wastewater Using Small-Scale Gradual Hydroponics Planted with Duranta erecta, Addis Ababa, Ethiopia

This study aimed to evaluate the treatment potential of gradual hydroponics planted with Duranta erecta in the removal of pathogens from domestic wastewater. Two experimental and control units were configured in series. Each unit contains three bioreactors and was arranged in a cascaded configuration. The two experimental units used both plant and media, but the two control units used only media to treat the wastewater. Gravel and polyester sponge were used as media. Experimental unit 1 and control unit 1 used gravel as media; however, experimental unit 2 and control unit 2 used polyester sponges as media. The experiment was operated at hydraulic retention times of 1, 3, 5, and 7 days in a continuous mode. The performance of the hydroponic system was evaluated by characterizing the influent and effluent quality using standard methods. At optimum hydraulic retention time (7 days), the average removal of experimental units 1 and 2 was 98.7% and 89.8% for heterotrophic bacteria, 96.2% and 86.8% for total coliform, and 92.9% and 84.0% for fecal coliform, respectively. Analysis of variance showed that there was a significant difference P < 0.05 between the two experimental and control units in removing pathogens, but no significant difference P > 0.05 was observed between the two experimental units and between the two control units. Heterotrophic bacteria and coliforms were satisfactorily removed from domestic wastewater via a gradual hydroponic system. Hence, the hydroponic treatment system planted with Duranta erecta has a promising potential in the removal of pathogens from domestic wastewater in developing countries including Ethiopia.

Calculation of Intake Oxygen Concentration through Intake CO2 Measurement and Evaluation of Its Effect on Nitrogen Oxide Prediction Accuracy in a Heavy-Duty Diesel Engine

A new procedure, based on measurement of intake CO2 concentration and ambient humidity was developed and assessed in this study for different diesel engines in order to evaluate the oxygen concentration in the intake manifold. Steady-state and transient datasets were used for this purpose. The method is very fast to implement since it does not require any tuning procedure and it involves just one engine-related input quantity. Moreover, its accuracy is very high since it was found that the absolute error between the measured and predicted intake O2 levels is in the ±0.15% range. The method was applied to verify the performance of a previously developed NOx model under transient operating conditions. This model had previously been adopted by the authors during the IMPERIUM H2020 EU project to set up a model-based controller for a heavy-duty diesel engine. The performance of the NOx model was evaluated considering two cases in which the intake O2 concentration is either derived from engine-control unit sub-models or from the newly developed method. It was found that a significant improvement in NOx model accuracy is obtained in the latter case, and this allowed the previously developed NOx model to be further validated under transient operating conditions.

Smart in-cylinder pressure sensor for closed-loop combustion control

Our approach of a closed-loop combustion control is built on an intensively evaluated robust cylinder pressure sensor with integrated smart electronics and an openly programmed engine control unit. The presented pressure sensor consists of a steel membrane and a highly strain-sensitive thin film with laser-welded electrical contacts. All components are optimized for reliable operation at high temperatures. The sensor setup safely converts the in-cylinder pressure of a combustion engine at temperatures of up to 200 ∘C into the desired electrical values. Furthermore, the embedded smart electronics provides a fast analogue to digital conversion and subsequently computes significant combustion parameters in real time, based on implemented thermodynamic equations, namely the 50 % mass fraction burned, the indicated mean effective pressure, the maximum pressure and a digital value, which represents the intensity of knocking. Only these aggregated parameters – not the running pressure values – are sent to the engine control unit. The data communication between the smart sensor and the engine control unit is based on the controller area network bus system, which is widely spread in the automotive industry and allows a robust data transfer minimizing electrical interferences. The established closed-loop combustion control is able to control the ignition angle in accordance with the 50 % mass fraction burned at a certain crankshaft angle. With this loop, the combustion engine is controlled and run efficiently even if the ignition angle is intentionally incorrectly adjusted. The controlled and automatic correction of simulated ageing effects is demonstrated as well as the self-adjustment of an efficient operation when different fuels are used. In addition, our approach saves the computing capacity of the engine control unit by outsourcing the data processing to the sensor system.

Design and Construction of an ALD Reactor by Growth of Al2O3 Nanostructure Films

Objective: This project focuses on designing, building and commissioning work the atomic layer deposition (ALD) reactor for Al2O3 ultrathin film, which it will be contain specific components and a system's own control unit. Methodology: The ALD reactor was designed under a system to minimize components, flow lines and connections; to reduce manufacturing costs, volume of precursors, among others. Currently, ALD reactors are expensive to sell, maintain and replace parts. The design and manufacture of the ALD reactor manufactured at the University of Sonora (UNISON) is based on the state art with sequential binary reactions of the precursors, for the proposal for the manufacture of solar cells. Contribution: It was possible to build and commission the ALD reactor for the deposition of ultra-thin films, with the characteristics of being reproducible and scalable, which makes it attractive for commercialization. The homemade ALD reactor at UNISON is considered a very interesting equipment for the semiconductor research area, since it is possible to combine different types of materials in the form of films such as oxides and nitrides in the order of Angstroms (Ǻ).

Development of an Autonomous Driving Smart Wheelchair for the Physically Weak

People who have difficulty moving owing to problems in walking spend their lives assisted by wheelchairs. In the past, research has been conducted regarding the application of various technologies to electric wheelchairs for user convenience. In this study, we evaluated a method of applying an autonomous driving function and developed an autonomous driving function using ROS. An electric wheelchair with a control unit designed to enable autonomous driving was used to test the basic performance of autonomous driving. The effectiveness of the technology was confirmed by comparing the results of autonomous driving with those of manual driving on the same route. It is expected that the evaluation and improvement of the usability and ride quality as well as additional studies will help improve the mobility convenience of physically disabled persons.