Transforming Detection Metrics: How ML-Driven Technology Helped our Client Identify 30+ Smells with >90% Accuracy
The Nose Knows, But Technology Can Help It Know Better
The client operates in the domain of innovative solutions using smell technology and neurotech IoT devices. Their applications span various industries, including agriculture, global shipping, and healthcare. The client knew the limitations of traditional smell detection. It’s slow, unreliable, and often can’t handle the complexities of the real world. They needed a sharper tool – something with a nose for opportunity. They needed a system that could:
Identify a broader range of smells with higher accuracy.
Analyze smell concentration for more precise results.
Deliver real-time data for faster decision-making.
Be portable and user-friendly for diverse applications.
Their mission? To revolutionize smell detection across various industries – and with our AI-powered solution, they did just that. Sensors are placed on animal noses, collecting electrophysiological data as they sniff out various objects. This data, rich with information about the smells they encounter, became the training ground for our AI hero – a multi-class classifier with autoencoders.
By the numbers
Accuracy on Point:
Forget unreliable sniff tests – our solution boasts an impressive >90% accuracy rate in identifying different smells
Big Data, Big Results:
We tackled a massive data challenge, processing over 20 GB of datasampled at a rapid 5 kHz for robust model training
A Diverse Smelling Spectrum:
No smell is left behind! Our system successfully identified a wide range of>30 different smellsfor various objects.
Indium’s Innovation Engine: Powering The Future of Smell Detection
At Indium, we believe in pushing the boundaries of what’s possible. For this project, we designed a comprehensive solution that revolutionizes smell detection. The power of this solution wasn’t just in its accuracy. We built a user-friendly mobile app with integrated ML models. This allowed users to interact with the system and receive real-time results, streamlining the entire odor detection process:
ML-driven smell detection app with mobile interface
We built a cutting-edge application powered by machine learning. This app analyzes data collected from sensors placed on animals’ noses, enabling real-time smell classification. The user-friendly mobile interface ensures convenient interaction and instant access to results.
Unlocking the power of animal noses
We leveraged biomimicry by strategically placing electrophysiological sensors on animals’ noses. These sensors capture the electrical signals produced when the animal smells something, providing a wealth of objective data for analysis.
Multi-class classifiers with autoencoders
The raw sensor data is fed into a powerful AI model – a multi-class classifier with autoencoders. This sophisticated model is trained to decipher the electrical signatures and categorize them accurately. The result? An incredibly detailed picture of the specific smell being detected, along with its concentration.
Mobile app for real-time results
Seamless integration between the AI models and a user-friendly mobile application is a cornerstone of this solution. The mobile app empowers users to interact with the system and receive results instantaneously, maximizing efficiency in field applications.
Industry-specific applications
The true potential of this solution lies in its versatility. We designed it for scalability across various industries. The applications are vast, from determining soil quality in agriculture and early detection of crop diseases to identifying illegal substances, chemicals, and radioactive waste in global shipping. The healthcare field holds particular promise, with the potential for early disease detection through smell analysis.
The Proof is in the (sniffable) Data
Over 90% Accuracy
Our solution achieved an impressive accuracy rate, sniffing out the correct smell over 90% of the time.
Big Data Power
We processed a massive 20 GB of data, all meticulously sampled at a high rate of 5 kHz. This robust dataset fueled the power of our machine learning models.
A Universe of Smells
The system successfully identified a diverse range of over 30 different smells, proving its ability to handle a wide variety of smell detection tasks.
About Indium
Indium is an Al-driven digital engineering company that helps enterprises build, scale, and innovate with cutting-edge technology. We specialize in custom solutions, ensuring every engagement is tailored to business needs with a relentless customer-first approach. Our expertise spans Generative Al, Product Engineering, Intelligent Automation, Data & Al, Quality Engineering, and Gaming, delivering high-impact solutions that drive real business impact.
With 5,000+ associates globally, we partner with Fortune 500, Global 2000, and leading technology firms across Financial Services, Healthcare, Manufacturing, Retail, and Technology-driving impact in North America, India, the UK, Singapore, Australia, and Japan to keep businesses ahead in an Al-first world.
