Artificial intelligence, connected sensors and big data analytics are reshaping how cities manage drinking water and treat sewage, but a new study finds that critical gaps in sewage infrastructure, cybersecurity and equity threaten to limit the benefits of that transformation.
A systematic literature review published in the journal Water mapped how Industry 4.0 technologies are being deployed across urban water and sanitation systems. Researchers at Santa Catarina State University (UDESC) in Brazil analysed 208 peer-reviewed articles published between 2019 and 2024, covering applications from water distribution and leak detection to wastewater treatment and consumption measurement.
AI and IoT lead the way, but not uniformly
Three technologies dominate the evidence base. Artificial intelligence accounted for 43% of all recorded occurrences, followed by big data and data analytics at 26.5% and the internet of things (IoT) at 19.8%. Together, they represent nearly 90% of all identified applications.
IoT stood out as the most versatile, being the only technology documented across every application area examined: from water distribution and wastewater treatment to sewage collection and smart metering. In practice, networks of sensors embedded in pipes, pumps and treatment plants provide operators with real-time data on pressure, flow rates and water quality that traditional monitoring methods cannot match. One study cited in the review found that IoT-enabled wastewater monitoring systems achieved efficiency levels approaching 88.7% and recycling rates of up to 96.3%. Another recorded a 95% success rate for IoT-based smart metering in detecting residential leaks.
While Industry 4.0 technologies are moving sanitation services from reactive to predictive management, stronger policy support, investment in sewerage infrastructure and sector-specific cybersecurity frameworks are needed
Artificial intelligence is being applied to leakage control by detecting anomalies in pressure and flow data, enabling faster localisation of losses and reducing non-revenue water. In wastewater treatment, the second most common application area after water distribution, AI models predict dissolved oxygen and nitrate concentrations, optimise biological processes and support regulatory compliance. Big data underpins both: one pipeline condition assessment model was trained on a dataset of 112,000 recorded pipes; another used approximately 17 million household measurements to predict water quality at the consumer level.
Where digital tools are failing to reach
Despite significant progress in some areas, the review identifies clear gaps. Sewage collection, the pipes and infrastructure that carry wastewater away from homes, received only a single occurrence across the entire sample. The authors point to a familiar set of barriers: insufficient public policy and institutional support, shortages of qualified professionals, high maintenance costs and limited community engagement. In Brazil, the domestic wastewater of 45% of the urban population remains untreated.
Cybersecurity is another underexplored area. As sanitation infrastructure becomes more connected, it also becomes more exposed to digital threats, yet the review finds that security-related applications remain limited and that most utilities rely on generic information security frameworks not designed for the specific risks of water systems. Blockchain, appearing in just 2.7% of occurrences, was primarily associated with data integrity and critical infrastructure protection, but its overall adoption remains low. Augmented reality and robotics barely featured, at 1% and 0.3% of occurrences, respectively.
The study also raises a governance concern: AI-based decision-support tools that draw on aggregated data without disaggregating by sex and gender risk overlooking the needs of women, who bear primary responsibility for household water management in many parts of the world. Policies on tariffs, water-saving programmes and infrastructure investment shaped by incomplete data, the authors argue, may reinforce rather than reduce existing inequalities.
The authors conclude that while Industry 4.0 technologies are moving sanitation services from reactive to predictive management, stronger policy support, investment in sewerage infrastructure and sector-specific cybersecurity frameworks are needed to ensure that the benefits are distributed across the entire urban water cycle.
