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This paper intends to conceptualise an optimisation solution for vehicle routing that can get the best routing result and release the most optimal route to the driver, namely WeRoute. The objectives of the paper are to manage the data efficiently, save time, reduce cost, enhance customer satisfaction, and decrease the emission of carbon. Moreover, this is also known as the vehicle routing problem, which deals with a range of variables, including drivers, stops, roads, and customers. The method, Genetic algorithm, was developed to improve the efficiency of generating feasible routes for a project. A team of drivers and several stops are needed to generate the solution of optimising the vehicle routing. It can be said that the more drivers or stops, the more complicated the problem becomes, such as cost controls and vehicle limitations. Thus, a route optimisation tool slowly becomes the key to ensuring the delivery business as efficiently as possible.

The paper describes based on techniques on the air pollution data visualization. This approach involves graph plotting algorithms with parallel coordinates that explore the raw data with interactive filtering that facilitates the insight of the materials that mixed and harm the population in northern Malaysia. By presenting the parallel coordinates method to visualize the parameter space that influence and visually identify the hazardous, moderate, unhealthy gaseous content in the air. The paper discusses the performance of the chosen visualization method and tested with northern region datasets.