Smart Waste Management : "With the help of AI, waste data can be better understood, interpreted and predicted"

Garry Nemack, Teamleiter Vertrieb & Vertragsmanagement Standard der Axians eWaste
© Axians

Can you explain the concept of data-driven waste management technology and how it differs from traditional waste management approaches?

With our waste management solution eNATURE, waste and disposal data are recorded and documented based on user rights, master data, origins, and predefined disposal routes. This means that the required key figures for evaluations and logistical processes are predefined, available everywhere, and stored transparently and comprehensibly.

What types of data are typically collected in data-driven waste management systems, and how is this data used to make informed decisions?

Waste-specific data, disposal logistics data, and commercial information are recorded. The data is used for

  • support in purchasing processes for waste management services
  • contract management with external disposal service providers
  • the control and monitoring of internal logistics processes
  • the control and monitoring of external disposal processes
  • internal and external waste management and sustainability reports
  • official obligations to provide evidence

Related article: The Future of Recycling: Robots on the Rise

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Managing and analyzing large amounts of data requires careful data collection, cleansing, and integration. - © ING Studio 1985 -

What challenges are associated with managing and analyzing large volumes of data generated by data-driven waste management systems?

Managing and analyzing large amounts of data requires careful data collection, cleansing, and integration. Furthermore, the data must be protected from unauthorized access, manipulation, or loss. The data should be presented in an understandable and usable form, e.g. through visualization, reporting, and dashboard tools such as those provided by our eNATURE solution.

What steps are typically taken to ensure that data collected and analyzed in waste management processes is both reliable and relevant?

In the area of master data, our eNATURE solution relies on import interfaces to systems in which validated data is available. In the operational area, interfaces to ERP systems (such as SAP), weighing equipment, container level sensors, RFID systems, barcode systems, etc. reduce the risk of incorrect entries, ensure timely availability of data, and significantly reduce the manual data entry effort.

Are there any regulatory or compliance aspects that need to be considered when implementing data-driven waste management technologies, especially when dealing with sensitive waste data?

When introducing data-driven waste management technologies, national and international requirements for data protection and data security must be considered. These relate in particular to the legality, transparency, purpose limitation, data minimization, accuracy, storage limitation, integrity, and confidentiality of the data. For example, our eNATURE solution uses two-factor authentication (2FA). This ensures that the data is secure in transmission and storage through authorization and encryption.

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Data protection and security play an important role, as these technologies often collect, process, and transmit sensitive data about waste producers, collectors, and recyclers.

What role do data privacy and security play in the implementation of smart waste management technologies?

Data protection and security play an important role, as these technologies often collect, process, and transmit sensitive data about waste producers, collectors, and recyclers. This data can be, for example, personal data, company secrets, or environmental data that require a high level of protection against unauthorized access, manipulation, or loss.

To ensure adequate data protection and security, various aspects must be considered during implementation, such as the application of technical and organizational measures that ensure an adequate level of protection for the data. This includes, for example, encryption, authentication, access control, data backup and contingency planning, and many more. Furthermore, the rights and interests of affected companies must be taken into account, such as information, consent, correction, and deletion of data. Axians eWaste ensures this, for example, through corresponding certifications according to ISO 27001 and 5001.

What are some of the potential environmental and economic benefits of implementing smart waste management systems in urban areas?

Benefits include reducing greenhouse gas emissions by optimizing transport processes. Furthermore, systems such as eNATURE help to avoid, separate, or prioritize the recycling of waste by providing information such as waste quantity, quality, and destination. Smart waste management systems can also create new employment and business opportunities in environmental engineering and resource efficiency by increasing demand for innovative products and services related to waste management.

Read more on the topic in our previous business talks here and here!

Route optimisation ultimately helps save money.

- © Andrii Yalanskyi -

What role does the Internet of Things (IoT) play in connecting various elements of waste management, such as waste bins, collection vehicles, and central monitoring systems?

By using, for example, sensors, RFID, GPS, mobile radio, and other technologies, these elements can collect data on their condition, location, fill level, weight, and other parameters and exchange them via the internet. This enables better planning, control, and optimization of waste management processes.

By networking waste containers with intelligent systems, waste producers can be informed about the correct waste separation, avoidance, and recycling. Furthermore, waste containers can provide information about the content quantity and/or the quality of the waste and thus initiate a disposal order themselves.

By networking waste containers with collection vehicles, waste collectors can be informed about the fill level, contents, and location of the waste containers. Among other things, this enables more efficient route planning.

In waste recycling, by networking collection vehicles with central monitoring systems, waste recyclers can be informed about the quantity, quality, and origin of the waste. This enables better sorting, a higher recycling rate, and more transparent waste traceability.

What advice would you give to municipalities or waste management companies that are considering transitioning to a smart waste management approach?

We recommend seeking advice from competent IT service companies with relevant industry experience and getting appropriate advice.

Related article: "Smart waste management promotes recycling and reduces operational costs"

Using AI, waste data will be better understood, interpreted, and predicted in the future.

How do you foresee data-driven waste management evolving in the future, and what new possibilities do you see on the horizon?

In our opinion, data-driven technologies for waste management will develop rapidly in the future and offer numerous new opportunities, such as:

  • Using AI, waste data will be better understood, interpreted, and predicted in the future. This will lead to better planning, optimization, and decision-making in waste management. For example, AI will be used to analyze and predict waste generation, waste composition, waste quality, waste recovery options, and waste impacts.
  • Using IoT in conjunction with cloud computing will connect and control the different elements of waste management. This will lead to increased flexibility, scalability, and automation of waste management.