Mutunga Titus, Sinanovic Sinan, Harrison Colin S
School of Engineering and Built Environment, Glasgow Caledonian University, Glasgow G4 0BA, Scotland, UK.
Sensors (Basel). 2024 May 17;24(10):3191. doi: 10.3390/s24103191.
Water constitutes an indispensable resource crucial for the sustenance of humanity, as it plays an integral role in various sectors such as agriculture, industrial processes, and domestic consumption. Even though water covers 71% of the global land surface, governments have been grappling with the challenge of ensuring the provision of safe water for domestic use. A contributing factor to this situation is the persistent contamination of available water sources rendering them unfit for human consumption. A common contaminant, pesticides are not frequently tested for despite their serious effects on biodiversity. Pesticide determination in water quality assessment is a challenging task because the procedures involved in the extraction and detection are complex. This reduces their popularity in many monitoring campaigns despite their harmful effects. If the existing methods of pesticide analysis are adapted by leveraging new technologies, then information concerning their presence in water ecosystems can be exposed. Furthermore, beyond the advantages conferred by the integration of wireless sensor networks (WSNs), the Internet of Things (IoT), Machine Learning (ML), and big data analytics, a notable outcome is the attainment of a heightened degree of granularity in the information of water ecosystems. This paper discusses methods of pesticide detection in water, emphasizing the possible use of electrochemical sensors, biosensors, and paper-based sensors in wireless sensing. It also explores the application of WSNs in water, the IoT, computing models, ML, and big data analytics, and their potential for integration as technologies useful for pesticide monitoring in water.
水是维持人类生存不可或缺的资源，因为它在农业、工业生产和家庭消费等各个领域都发挥着不可或缺的作用。尽管水覆盖了全球71%的陆地表面，但各国政府一直在努力应对确保提供安全的生活用水这一挑战。造成这种情况的一个因素是现有水源持续受到污染，使其不适于人类饮用。农药是一种常见的污染物，尽管它们对生物多样性有严重影响，但却不常进行检测。在水质评估中测定农药是一项具有挑战性的任务，因为提取和检测过程复杂。尽管它们有有害影响，但这降低了它们在许多监测活动中的受欢迎程度。如果利用新技术对现有的农药分析方法进行改进，那么就可以获取有关它们在水生态系统中存在情况的信息。此外，除了无线传感器网络（WSN）、物联网（IoT）、机器学习（ML）和大数据分析集成所带来的优势外，一个显著的成果是在水生态系统信息方面实现了更高程度的精细化。本文讨论了水中农药检测的方法，强调了电化学传感器、生物传感器和纸质传感器在无线传感中的可能应用。它还探讨了无线传感器网络在水中的应用、物联网、计算模型、机器学习和大数据分析，以及它们作为对水中农药监测有用的技术进行集成的潜力。
