How to achieve 99% accuracy in air quality monitoring with supervised learning
Recent strides in the efficacy of AI have made it possible to mitigate risks associated with poor air quality. Real-time air particle monitoring means we
SMART ENVIRONMENTAL MONITORING
Unearth Real-Time Insights with AI.
Our world is complex. Let Deep Learning reveal it.
Welcome to the place where meaningful ideas are nurtured,
transformed and launched.
With Deep Learning, sensors get better over time
Achieving Pinpoint Accuracy with AI-Driven Data Analysis
Artificial Intelligence is changing how we monitor our environment.
While sensors can reveal a certain amount about environmental conditions and their impact our health and well being, AI – and in particular Deep Learning – increases the accuracy of sensors over
time.
Change how you maintain and manage your sensors
More accurate, more valuable. For you and the planet.
When it comes to health and safety, your data can never be too accuarte. Our Deep Learning solutions have a proven track record in optimising environmental monitoring.
Noise And Audio
Speed-up decision making with automated noise-source classification. Benchmark environmental noise policies.
- Audio labelling
- Root-cause analysis
- Trend-analysis
Hydrology & Air Quality
Reduce maintenance costs.Increase robustness of air quality sensors in high-humidity conditions.
- Predictive maintenance
- Measurement in harsh conditions
Geohazards
Early warnings of natural events. Risks analysis using high-resolution image.
- Decision support
- Risk assessment
Deep learning for Machinery Manufacturing
Benefits
Data Quality
Increase accuracy of sensors in
the toughest conditions.
Resilience
Reduce sensors downtime and minimize maintenance cost.
Actionable Insights
Enable your clients to take fast pace, data-driven decisions.
Examples
An AI-powered landslide monitoring technique which saves lives
Landslides are one of the most frequent geological events worldwide. Between 1998 and 2017, they killed 18 thousand people and affected 4.8 million lives. In addition,
A new noise API for sound classification in building sites
Noise pollution monitoring devices manufacturer Sonitus Systems partnered with Sparkd to design a noise API which automatically recognises and labels sounds. Noise levels on construction
