Oslo-based trashtech startup Sensorita uses intelligent, data-driven sensors to accurately measure waste levels in open skips and large containers. By providing real-time data on location, fill levels, and waste quality, this solution aims to reduce contamination and make collection more efficient during the recycling process. How exactly does it work, and what effect could it have on our recycling systems? We spoke with Ulrikke Lien, the company’s co-founder and CEO, to find out.
Let’s start with a general overview – please could you introduce Sensorita and its core technology to us?
Sensorita is a trashtech startup that I founded in 2020, back when I was a student at the Norwegian University of Life Sciences in Oslo. Our company has developed a new sensor technology that creates digital twins of skips and roll-offs by measuring location and fill levels of these waste containers.
This is achieved through a cutting-edge, AI-powered technological solution that uses a highly advanced radar sensor that is affixed to the side of the container. Machine learning algorithms trained on over a million data points then measure fill levels of skips.
The sensor provides a comprehensive real-time data view and inventory of each container which enables customers to make informed decisions about their skips and when collections should be made and even automatically place collection orders.
Every physical radar and GPS sensor creates a digital twin of the waste container which allows all the data to be processed and displayed. The data shows location, fill level, and will even soon be able to reveal the actual contents of the skips.
The benefit of this technology is essentially two-fold, with radar sensor technology allowing for accurate, real-time information and data gathering, empowering customers to optimise waste production and streamline distribution which otherwise wouldn’t be possible.
Additionally, the sensor is fitted with high-level GPS, which combats the problem of missing, misplaced, or unused skips. The GPS data, coupled with the radar sensor, ensures that the location of each container is accounted for, whilst also playing an instrumental role in locating the container for efficient automated collection.
Why have you chosen to tackle this particular issue in waste management, and what makes it so important?
Around the world, recycling rates are much lower than they could be. For example, of the 26 million tonnes of waste produced in the UK, 12 million tonnes are recycled, and 14 million tonnes are sent to landfill sites. This gives an average recycling rate of just 45%, and amounts to the weight of around 260 large cruise ships of waste materials.
Waste management has up to now operated with a severe lack of data-driven insights. The contents and fill levels of commercial skips and roll-offs are a mystery and in some cases they even go missing.
This haphazard approach means unnecessary removal or inspection journeys are the norm. Using our technology, we can provide companies with the information required for a streamlined, data-driven, and sustainable waste management solution, which in turn unlocks a vast untapped pool of resources to be put to good use.
This feeds into our critical mission to not only maximise resource utilisation and promote sustainability, but to also provide companies with the information they need to tackle their waste issues head-on.
Could you take us behind the scenes on the history of the business? What were some of the key technological hurdles you had to overcome during the development of the technology?
Sensorita’s journey began in 2020 when Ragn-Sells, one of the largest waste management companies in the Nordics, approached me with a challenge: how to measure waste levels in open containers. Intrigued by the problem, I turned it into my Master’s thesis, exploring the potential of radar and machine learning to solve this issue. What started as academic research quickly grew into a business with a bold vision to revolutionise waste management.
The first major hurdle came in 2021 when we had to prove that radar technology could reliably predict fill levels in containers. With support from the Norwegian Research Council and a development partnership with Ragn-Sells, we developed an initial prototype of the sensor and machine learning algorithm. Our early focus was on refining the algorithm to process radar data effectively, laying the foundation for Sensorita’s offering.
By 2022, we were ready to validate the technology in a controlled environment. Collaborating closely with Ragn-Sells, we conducted lab-based tests, collected and manually labelled data, and refined our fill-level predictions.
The biggest challenge was achieving consistent accuracy across different container types, waste materials, and environmental conditions. This phase allowed us to turn theory into a working solution that could reliably measure container fill levels.
In 2023, we aimed for CE certification of our sensors, a rigorous process requiring the design to meet strict safety and performance standards. Additionally, automating waste management at live construction sites brought new complexities as real-world environments introduced variability far beyond lab conditions.
For example, testing the system at the construction site of Oslo’s flagship swimming pool required us to adapt the technology to diverse waste streams and fluctuating usage patterns. On top of this, we began exploring waste fraction detection, using radar and machine learning to classify waste types. Early results were promising but required overcoming significant data challenges, including collecting and labelling large datasets in the field.
By 2024, our CE-certified sensors were in mass production, and we had successfully rolled out the solution across 550 containers in one Ragn-Sells department. This deployment validated not only the fill level predictions but also the broader efficiency gains for waste management.
Achieving scalability was a major hurdle - our hardware had to be robust, cost-effective, and adaptable to large-scale operations. The strong demand from Ragn-Sells, including an initial rollout of 2,550 sensors across their operations, showed we had succeeded.
What are some past or ongoing projects Sensorita has been involved in that you are particularly proud of, and what have you learned from them?
Currently, we are excited to be involved with Ragn-Sells, such a reputable and recognisable brand in Scandinavia. Our technology has been rolled out in the form of over 2,500 Sensorita units across Norway during its first year of deployment.
It is very motivating to see how the solution has been received in the market as well as improving and automating waste management at various sites ranging from large industrial sites to smaller workshops and commercial sites.
What can we expect from Sensorita in the coming months and years, and how are you planning to scale outside of Norway? What are some of the key differences in terms of how the Norwegian and EU waste management industries operate?
Our major upcoming innovation is the advancement of our machine learning algorithms to the point where we will be able to use them to ascertain the actual content of skips and waste containers, as well as the fill level and location. This represents a significant step in allowing waste management companies to make truly informed and effective decisions.
Norway has seen remarkable success in recycling, with a deposit return scheme that leads to 97% of all plastic drink containers being returned and 92% repurposed. This achievement is driven by strong industry engagement and supportive legislation due to major tech innovations, setting a standard for effective waste management.
We see the same challenges across Europe when it comes to streamlining waste management and offering a better customer experience. With the technology and solution validated in Norway, we are ready to expand to other European countries.
We are also currently using the data collected by the sensors to build software that will help waste companies make smarter, automated decisions. The platform will enhance the user experience by offering proactive communication via a mobile app, with the data also being accessed through APIs to ensure the seamless integration with other software systems.
We want to empower waste management companies with the best tools to offer best-in-class services to their customers.
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