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    AIoT in Environmental Sustainability
    (IGI Global, 2025) Rushda Sharf, Yusra Sharf
    To address the majority of environmental sustainability issues, like transportation, energy, water management, and biodiversity, artificial intelligence (AI) has grown in importance. The primary focus areas in energy are area neural networks, expert systems, fuzzy logic models, and pattern recognition. This chapter assesses how the use of AI could improve the environment by reducing the effects of agriculture, climate change, water resources, weather forecasting, ocean health, and disaster resilience. The impact of AI on the environment and its sustainable applications are examined in this chapter using qualitative analysis. With an emphasis on AI's role in advancing environmental sustainability, the chapter's main goal is to identify applications of AI for environmentally friendly practices. It can help stakeholders understand international initiatives to improve environmental sustainability by utilizing AI.
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    Mixed Traffic Modelling: An Overview of Car Following and Lane Change Models
    (IGI Global, 2024) Mohd Sadat; Syed Aqeel Ahmad,Mehmet Ali Silgu
    Traffic modelling has gained importance due to the adoption of intelligent transportation systems and software based on traffic models providing a platform to test and improve such systems. Modelling mixed traffic has proved to be a challenging task due to variations in vehicle dimensions and composi- tion along with non-lane-based driving. Most of the simulation software is based on the car following models and lane change models which were originally developed for lane-based traffic. Several attempts have been made to adapt these models for mixed traffic by extending them to include new parameters.This study summarizes lane change models used along with car following for mixed traffic. It can be concluded from past studies that lateral manoeuvre varies with the longitudinal speed in a non-linear manner. Sub-models or specific parameters are needed to model the lateral behaviour of each class of vehicle. Trajectory data analysis and subsequent models have also pointed towards the need for vehicle pair-dependent parameters.