Guth David, Herák David
Department of Mechanical Engineering, Faculty of Engineering, Czech University of Life Sciences Prague, 165 00 Prague, Czech Republic.
Sensors (Basel). 2025 Mar 20;25(6):1925. doi: 10.3390/s25061925.
Access to clean water remains a critical global challenge, particularly in under-resourced regions. This study introduces an autonomous water treatment system leveraging Industry 4.0 technologies, including advanced smart sensors, real-time monitoring, and automation. The system employs a multi-stage filtration process-mechanical, chemical, and UV sterilization-to treat water with varying contamination levels. Smart sensors play a pivotal role in ensuring precise control and adaptability across the entire process. Experimental validation was conducted on three water types: pond, river, and artificially contaminated water. Results revealed significant reductions in key contaminants such as PPM, pH, and electrical conductivity, achieving water quality standards set by the WHO. Statistical analyses confirmed the system's reliability and adaptability under diverse conditions. These findings underscore the potential of smart, sensor-integrated, decentralized water treatment systems to effectively address global water security challenges. Future research could focus on scalability, renewable energy integration, and long-term operational durability to enhance applicability in remote areas.
获得清洁水仍然是一项严峻的全球挑战,尤其是在资源匮乏地区。本研究介绍了一种利用工业4.0技术的自主水处理系统,包括先进的智能传感器、实时监测和自动化。该系统采用多阶段过滤工艺——机械、化学和紫外线杀菌——来处理不同污染水平的水。智能传感器在确保整个过程的精确控制和适应性方面发挥着关键作用。对三种水类型进行了实验验证:池塘水、河水和人工污染水。结果显示关键污染物如百万分率、pH值和电导率显著降低,达到了世界卫生组织设定的水质标准。统计分析证实了该系统在不同条件下的可靠性和适应性。这些发现凸显了智能、集成传感器的分散式水处理系统有效应对全球水安全挑战的潜力。未来的研究可以集中在可扩展性、可再生能源整合以及长期运行耐久性方面,以提高在偏远地区的适用性。