Aya Data

Overview:

The electric scooter market is booming and is expected to reach $34.7 billion by 2028, growing at an annual rate of 7.6%. This surge is transforming urban transportation, affecting everything from public transit to city infrastructure, and notably, how self-driving cars are trained to ensure safety.

With more e-scooters on city streets, regulations are struggling to keep up. City planners are working to figure out the best ways to manage this new technology while keeping everyone safe.

As the number of e-scooters grows, it’s crucial for AI companies to adapt to the rise in short-distance vehicles. They need to stay updated on new laws, common human behaviours, and ensure that self-driving cars can navigate safely in urban environments.

Challenge:

The Client needed to address a new challenge in training their self-driving car systems: the growing presence of e-scooters on European roads. Existing open-source data lacked sufficient examples of e-scooters and had inconsistent labels.

The task was to create a comprehensive dataset that would help self-driving car models recognize and predict the movements of e-scooters.

Solutions:

Aya Data’s experts labelled 10,000 images featuring e-scooters in various settings and situations. Each e-scooter was marked and categorised by type and other relevant details.

Results:

The labelled images were used to train the Client’s computer vision system. This improved the system’s ability to detect e-scooters in real time with 95% accuracy.

Ready to enhance urban mobility with advanced technology? Contact us to discover how our solutions can improve the safety and efficiency of autonomous vehicles.

Overview:

AI and machine learning are revolutionising medical diagnostics by analysing images from various medical scans, such as X-rays, MRIs, and CT scans. For instance, Google DeepMind has shown exceptional accuracy in diagnosing complex eye diseases using OCT scans.

By integrating AI in medical imaging, healthcare professionals can focus more on patient care and research, rather than getting bogged down with diagnostics. This accelerates the diagnostic process and ensures patients receive timely treatment.

Our Client, a European MedTech company, aimed to gather and annotate 3D scans of blood vessels (DICOM format). Their goal was to develop models to study how these vessels might be affected by invasive surgery.

Challenge:

Gathering medical data is challenging due to strict privacy and data protection regulations. Companies must obtain full consent for using personal data and ensure it is thoroughly anonymized.

Moreover, the task involved complex 3D annotations that required specialised medical knowledge. The Client was concerned about the high cost of hiring specialists who could provide the needed accuracy and quality.

Solution:

To address these issues, Aya Data collaborated with the Department of Radiology at the University of Ghana Medical Centre (UGMC). This partnership provided anonymized 3D vascular scans that filled gaps in the Client’s dataset.

Once the data was collected, Aya Data’s medical specialists used the Client’s platform to annotate the scans.

Results:

After several workflow refinements, the Client found that the annotations from Aya Data’s team were of equal or better quality compared to their European physicians, and at a significantly lower cost.

Aya Data maintains an ongoing partnership with the Client, continuing to provide medical data annotation and collection services.

Interested in efficient and cost-effective medical data solutions? Contact us today to learn how our services can enhance your healthcare projects.

Challenge:

Demeter, a company in West Africa that supplies organic fertilisers to small farmers, wanted to use soil acidity data to improve their sales. They knew that understanding soil conditions could help them recommend the right products to the right customers. However, they needed a way to combine soil acidity information with their customer and sales data to uncover valuable insights.

Solution:

Demeter partnered with Aya Data to develop a user-friendly dashboard that would merge soil acidity data with their customer and sales information. This interactive tool would allow them to:

– Visualise Data: See how soil acidity levels relate to their customers and sales.

– Analyse Relationships: Explore patterns between soil conditions, customer preferences, and product performance.

Aya Data collected the soil data from open sources and integrated it into the dashboard, creating a comprehensive and easy-to-use tool with interactive features and visualisations.

Results:

With the new dashboard in place, Demeter saw impressive improvements:

– Sales Growth: By understanding which products were needed where, Demeter increased their sales by 48% in just one year.

– Customer Engagement: Sales teams could now show farmers how soil acidity affected product effectiveness, boosting customer trust and loyalty.

– Smarter Decisions: The dashboard helped Demeter’s management make informed decisions on product development, market expansion, and inventory.

Thanks to the collaboration with Aya Data, Demeter successfully improved their sales strategy, better served their customers, and promoted their organic fertilisers more effectively.

Ready to optimize your agricultural product offers and better serve your customers? Get in touch with us today to learn how our solutions can transform your business insights and provide sustainable growth.