Smart highways endorse green and low-carbon handling construction infrastructures for promoting pollution-free environments and driving spaces. With the incorporation of artificial intelligence and smart computing features, sophisticated decision systems improve the aim of such smart highway constructions. For promoting green and low-carbon highway construction infrastructure, this research article introduces a pollution control-facilitated recommendation system (PCFRS). The system aims to satisfy eco-friendly driving demands and low-carbon emission requirements. In this system, eco-friendly driving demands and low-carbon emissions are the prime requirements for designing such highways. The research employs fuzzy control algorithms to analyze the relationship between green demands and demand satisfaction factors across different infrastructures based on policies from environmental departments and governing agencies. The green demands as formulated by the environmental department/ governing agencies are used for verifying the demand and relationship factors across various infrastructures. The fuzzy algorithm provides recommendations for optimal highway infrastructure design by identifying the maximum possible combinations of satisfaction factors, enabling cost-effective construction while meeting green environment and low-carbon emission goals. This process is aided by a fuzzy control algorithm with the relationship and demand factor as crisp inputs. The decisions on the maximum possible combinations of the satisfaction factor are used for infrastructure recommendations. The need for optimal design and promoting green environments are optimal across various highway lanes.