ARIKI
Automated remote inspection of critical infrastructures using intelligent camera systems for continuous monitoring of safety-relevant areas in wastewater management.
Four central problem areas of the current wastewater management are addressed in the ARIKI project: security of supply, economic efficiency, sustainability and digital operating concepts. The automated, digital monitoring enables a qualitative improvement of the Security of supply and at the same time ensures simplified compliance with the self-monitoring regulation for the operators. The early detection of damage to the systems ensures increased operational reliability and prevents costly repairs.
Furthermore, by reducing the necessary on-site inspections, a reduction in operating costs and an increase in Cost effectiveness reached. The improved economy leads to positive sustainability effects, including reducing carbon emissions, improving the climate footprint, reducing health risks and anticipating and remediating environmental damage such as sewage infiltration.
Another goal of the project is to create a new one digital operating concept as a reference architecture for European operators of water infrastructure, which includes AI-supported evaluations of real-time data and the detection of irregularities in operational processes. The ARIKI project is thus helping to pave the way towards digitized and sustainable wastewater management in Germany and the EU.
Our role in the project
The participation of the August-Wilhelm Scheer Institute gGmbH in the ARIKI project focuses in particular on the conception, camera system & edge computing, AI system for automated system monitoring and participation in the management & analytics portal. Above all, this creates the technical basis for the project, which is necessary to achieve the overriding goals.
Concepts
Goal: A detailed requirements analysis and a concept of the overall system as well as all individual components are created. In addition, the use cases for monitoring should be defined. System components and their interfaces are mapped in an overall architecture.
Result: Overall concept, technical requirements concept, catalog of duties and encumbrances, mock-up, definition of the system architecture and interfaces
Camera and Edge Computing
Goal: Existing hardware platform nCam is used for:
- Data collection and annotation of both non-critical and critical system parameters
- remote connectivity for encrypted transmission of video material and for system updates
- Installation of project-specific software components (AI models)
- Extension for 5G connectivity
- remote backup function to improve reliability
- IOT connectivity for sending and receiving push notifications with system status and process data
- Interface in graphic process visualization solutions (dashboard)
- Adaptation of the industrial interfaces to industry standard process control systems (PLC)
Result: Extended hardware platform, installation of necessary functionality on the camera system used, generation of training data, annotation of the training data, edge computing module
AI systems
Goal: Development of image-based AI models for monitoring the test facility.
Procedure: For this purpose, the data is first pre-processed based on the use cases and technologies used, thus increasing the data quality. Various experiments for image-based detection and localization of certain relevant events and states are used. Transfer learning is used as a training method in order to achieve generalizability beyond the defined use cases and to record even rare or complex states.
Result: Software component for automated system monitoring based on developed AI systems
Management and analytics portal
Objective: Development of a portal for information processing and presentation of the analysis results for the operating staff, for the deployment of the Edge AI modules, for the aggregation of data, for the management of the Edge devices, connection of third-party data sources such as weather data, visual processing of the AI analyses, integration of the camera live stream, determination of points of interest and definition of suitable AI modules and actions. Development of reference architecture for water management.
Agenda: Conception of the IT architecture based on the requirements analysis and Gaia-X standards. Defining the function and features in user workshops. Agile software development with regular user tests.
Result: Management and Analytics Portal Software
The initial situation
Overview of the need for action
Water management in Germany makes a significant contribution to the health and quality of life of the population, to environmental protection and to the competitiveness of industry and commerce through the constant availability and usability of water. The German water supply and disposal is part of the critical infrastructure and is characterized by a special decentralized structure, which makes constant inspection and maintenance only possible with high operating costs. At the same time, operators of such systems are faced with even greater demands due to increasingly stringent requirements and regulations, such as the self-monitoring ordinance, and in particular the inspection effort is increased.
86.400 km travel distance pa
1.760 h travel time pa
18.352 kg CO2 emissions pa
Your contact person
ARIKI
Automated remote inspection of critical infrastructure
Dr. Agnetha Flore
agnetha.flore@aws-institut.de
+49 173 7220 978
Your contact person
ARIKI
Automated remote inspection of critical infrastructure
Dr. Agnetha Flore
agnetha.flore@aws-institut.de
+49 173 7220 978
Our solution approach in focus
The operation of critical infrastructure such as sewage treatment plants, pumping stations or water treatment plants requires regular on-site inspections to ensure their operational and supply security. Water suppliers and wastewater associations with a large supply area usually operate many decentralized and remote plants that are usually unmanned. For inspection and maintenance purposes, these must be approached regularly, sometimes on weekdays, in order to comply with legal requirements and to ensure operational safety.
Remote monitoring using modern camera systems and a local, AI-supported evaluation could automate the routine inspection and significantly relieve the operator in terms of personnel costs and CO2 emissions. Critical points are automatically and regularly recorded by a camera and evaluated directly on site by an artificial intelligence using edge computing. In this way, damage or conditions are immediately recognized and reported to the responsible persons, who can then initiate appropriate measures.
The project aims at the application domain of water supply and water disposal and is accompanied by corresponding associated partners who provide their systems and data. Due to the high social relevance of the project, it should serve as a lighthouse in water management and have a projection effect on other sectors with similar challenges. The combination of edge data processing of large amounts of video data and the provision of the results on a Gaia-X compliant cloud portal form the basis for a modern approach to sovereign data exchange and use. On the basis of the technology, the potential for new, sustainable business models should also be created, which have both an economic and ecological benefit and thus a direct influence on climate and environmental protection.
Funding notice
The ARIKI project is funded by the Federal Ministry for Economic Affairs and Energy.
Funding code: 01MD23002D
Running time: 01.03.2023-28.02.2026
