In this paper, we envision to illustrate the process to be used in developing a mobile application on the smart contract. We start by looking at what other researchers have accomplished and how we can improve on what already exists. The paper highlights the requirement gathering process, the methodology for data collection to streamline and validate the requirement, the architecture and implementation phase by analyzing the technological stack to achieve the business goal.

Growing populations and environmental issues are a burden for urban transport systems. Current research fails to offer multimodal integrated solutions maximizing time, cost, emissions, and satisfaction. We introduce the first optimization model integrating carpooling with micro-mobility for multi-leg routing in dynamic urban conditions (peak, weather, accidents). In synthetically generated data calibrated with real-world trends, our framework performs up to 25% shorter travel times, 30% reduced peak-hour emissions, and sub-second computation for 40-node networks over single-mode baselines. The model’s scenario-aware flexibility and policy-controllable weights (${\lambda }_1$ to ${\lambda }_4$) offer planners a scalable solution for sustainable mobility. The paper’s primary contribution is its integrated optimization framework integrating carpooling, micro-mobility, and multi-leg routing in dynamic urban conditions, an absent component in prior single-mode or static models. Our scenario-based analysis demonstrates up to 30% travel time and emissions reduction over stand-alone mobility solutions.