Aims and scope
Wastewater spilling with suspicious or illegal substances poses a serious global threat to human health. Sensor technologies enabling wastewater monitoring are an important tool that can help face this problem. In this challenge, we propose a dataset acquired in different laboratories around Europe through a proprietary sensor technology for the real-time detection and classification of ten wastewater dangerous “contaminants”.
Wastewater can be defined as water polluted by human activities as a byproduct of domestic, industrial, commercial or agricultural activities. Wastewater is unsuitable for its direct use as contaminated by different types of organic and inorganic substances that represent a hazard to public health and environment. For this reason they cannot be returned directly to the environment since the final deliveries such as land, sea, rivers and lakes are not able to receive a quantity of polluting substances greater than their self-purifying capacity without compromising the normal balance of the ecosystem. In a smart city framework, for example, it can be very interesting to map the wastewater collection system and detect sources of pollution within a metropolitan area, in order to optimize water treatment systems or identify anomalies in wastewater, which could indicate fraudulent spills.
Towards an end-to-end system
This work is part of a project where the ultimate goal is the creation of an end-to-end identification system (from sensing to classification) capable of detecting a predefined set of substances commonly considered as dangerous and indicative of an anomalous use of water. All the substances considered are characterized by complete solubility in water, which makes them more difficult to identify and filter.