Smart Electrochemical Sensors and IoT for Monitoring Heavy Metals in Nigerian Water: Review of Advances and Deployment Challenges

Background: Heavy metal contamination in Nigerian water bodies poses persistent environmental and public health risks. Traditional laboratory-based detection methods, while accurate, are limited by cost, accessibility, and real-time applicability, creating a need for advanced monitoring approaches. Objectives: This review systematically synthesises recent advances in smart electrochemical sensors integrated with Internet of Things (IoT) technologies for heavy metal detection, highlighting technological innovations, field applications, and unresolved deployment challenges in Nigerian aquatic environments. Methods: Peer-reviewed literature was systematically surveyed to synthesise advances in heavy metal contamination assessment and smart electrochemical sensing technologies relevant to Nigerian aquatic systems. Publications spanning the early 2000s to 2023 were retrieved from major scientific databases, focusing on (i) environmental and toxicological studies of heavy metal exposure, (ii) electrochemical sensor development, including nanomaterial-enhanced and screen-printed platforms, and (iii) IoT-enabled water quality monitoring architectures. Additional studies addressing energy infrastructure, connectivity, cost considerations, and capacity constraints in Nigeria were included to contextualise deployment feasibility. The collected literature was qualitatively analysed to identify technological progress, practical applications, and persistent research gaps. Results: Nanomaterial-enhanced electrodes, such as graphene, carbon nanotubes, and metal nanoparticles, improve sensitivity, selectivity, and detection limits for Pb, Cd, Hg, As, and Cr. Miniaturised platforms, including screen-printed and microfluidic sensors, facilitate portable and multiplexed detection. IoT integration enables real-time data acquisition, cloud-based analytics, and remote monitoring, demonstrated across the Niger Delta, mining-affected rivers, and urban-industrial water bodies. Field studies reveal high correlation with laboratory measurements but also highlight technical, infrastructural, and economic challenges, including biofouling, sensor drift, power and connectivity limitations, high costs, and limited local expertise. Regulatory gaps and lack of standardised protocols further constrain national-scale deployment. Conclusion: Smart electrochemical sensors with IoT integration offer transformative potential for continuous and distributed monitoring of heavy metal contamination in Nigerian water systems. Despite demonstrable field viability, unresolved gaps remain in autonomous operation, multiplexed detection, long-term stability, and data integration, indicating critical areas for further investigation to fully leverage these technologies for water quality management.