The rapid development of connected car technology imposes vital requirements to develop adaptive and robust intelligent computational models to help enhance communication, safety, and autonomous decision-making for vehicles. This paper deals with how to incorporate neuro-evolutionary computing-the hybrid paradigm of neural networks and evolutionary algorithms-into the connected car ecosystem. We thus propose a holistic framework that harnesses the adaptive learning capabilities of neural networks and the optimization strengths of evolutionary algorithms to ensure optimal real-time decision-making processes for efficient traffic management and safe passage by passengers. The framework houses a multi-agent system, wherein every connected vehicle is an intelligent agent in itself-learning and evolving toward dynamic traffic surroundings. We present simulations and experimental results showing the effectiveness of our neuro-evolutionary approach to reduce communications latencies and lead to better optimization of routes through proactive collision avoidance. From these results, it is suggested that there exists significant promise for neuro-evolutionary computing to address computational challenges in connected car networks, paving the way to safe, resilient, and efficient intelligent transportation systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

This preliminary study focused on assessing the carcinogenic and non-carcinogenic risk of residents due to heavy metal exposure in the indoor settled dust of 34 randomly selected households in Kampar, Perak, Malaysia. The indoor dust samples of residential houses (n=34) were collected and analysed for the concentration of heavy metals (Fe, Zn, Cu, Pb, Cr, Mn) using inductively coupled plasma mass optical emission spectrometry (ICP-OES). Health risk due to heavy metals exposure were assessed by determining the Carcinogenic Risk (CR), Hazard Quotient (HQ) and Hazard Index (HI). Results showed median concentrations of heavy metals in the indoor settled dust samples were in descending order of: Zn (6367.75 mg/kg) >Fe (2064.81 mg/kg) >Pb (59.22 mg/kg) >Cu (49.36 mg/kg) >Mn (41.97 mg/kg) >Cr (22.75 mg/kg). Carcinogenic risk (CR) of Pb and Cr of both adults and children were within the accepted limit (1 × 10-4 to 1 × 10-6). Whereas the HQ and HI of the heavy metals for both adults and children were below 1 which indicates there is no non-carcinogenic risk posed to the Kampar community. Nevertheless, this study provides crucial baseline data for researchers and government authorities in studying and developing indoor air quality relevant guidelines and regulations in Malaysia. © The Authors, published by EDP Sciences.