Eco-friendly environment concern contributes to the survival of life on earth. Monitoring chemicals produced by growth requires a multidisciplinary scientific approach. Climate change is a result of pollution and overuse, particularly in the air. Although government and industry have taken initiatives to limit air pollution, it is still necessary to check the quality of the air at ground level. The goal of this endeavour is to build intercommunication-based individual vehicle air pollution monitoring and identification by internet of things (IoT). Idling and accelerating conditions were recorded using tailpipe emission sensing. Authorities can act and assure upkeep if they are able to identify a car at a busy intersection; mobile connectivity enabled route and vehicle identification. In India, fewer people will die from air pollution because to data gathered in the cloud.

In this experimental investigation, rotary friction welding (RFW) was employed to fabricate dissimilar Al-Cu joints, and the RFW variables were rotated against the ultimate tensile strength (UTS) in an effort to strengthen the dissimilar AA1100 and pure copper (Al-Cu) joint using response surface methodology (RSM) with a three-factorial design. Following this, micro-hardness, metallurgical characterization, and fatigue properties studies were done on the dissimilar joints fabricated under the optimized conditions. As a result of this investigation, the UTS of 208 MPa was attained as a maximum as the rotation speed was set at 1800 rpm, the friction time was 10 s, and the forging load was 5 kN. The dissimilar joint exhibits a better fatigue strength of 98.5 MPa when compared to the AA1100 base metal. At optimized conditions, the feature of the fracture image was found to be brittle due to the development of new compounds in the weld interface. A significant dip in micro hardness (52 Hv) was noticed in the region that connects TMAZ and HAZ of the AA1100 side of the dissimilar joint, which was concluded to be the weakest zone as the dissimilar joints were fractured in the same location during the tensile test. The observed results benefit the automotive sector, especially when fabricating components that require effective thermal management and weight reduction, like electrical connectors, heat dissipation systems, and radiators. For heat exchanger applications, improved fatigue strength in dissimilar Al-Cu joints is important because it guarantees longer structural integrity and improved durability.

This article examines the properties of joints fabricated by friction welding (FW) using AA6061-T6 and AA7075 as examples of both similar and dissimilar metals. It also looks at how heat treatment after welding affects the metallurgical characteristics of the joint. The heat treatment method under investigation combines solutionizing heat treatment with synthetic ageing (STA). The tensile characteristics, microhardness, and microstructure of the as-welded and STA-treated welded specimens are assessed in the paper using mechanical testing equipment and metallurgical characterization methods. The findings demonstrate that the joint characteristics are enhanced by precipitate nucleation occurring in the joint interface of the FW similar and dissimilar joint under STA treatment. On the other hand, the STA influence on the tensile strength (TS) of joints made with AA7075 was greater than that of similar joints made with AA6061-T6, as well as dissimilar joints made with both AA6061-T6 and AA7075. Additionally, after STA treatment, the similar joints showed a uniform distribution of hardness. However, in the dissimilar joint after STA treatment, the hardness dropped suddenly on the AA6061-T6 side, specifically from the partially deformed zone (PDZ) towards the heat affected zone (HAZ).

Virtual prototyping has evolved to the automotive industry and allows for a more speedy and accurate car development process at a fraction of the previous costs. The application of virtual prototyping and utilization of computer aided design, simulations and digital twin has been discussed in this chapter. These approaches reduce development time and costs as well as improve design performance over traditional use of physical models. These tests add value to vehicle performance and safety so there are few tests such as crash, aerodynamics, and virtual assembly are discussed. It also introduces some recent tendencies on virtual prototyping development including Artificial Intelligence, Machine Learning and Virtual Reality. It identifies various challenges in applying these technologies and examines future prospects and implications in introducing them in automobile industry respectively.