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The Innovation Showcase
Design thinking is a non-linear, iterative process that teams use to understand users, challenge assumptions, redefine problems and create innovative solutions to prototype and test. Involving five phases—Empathize, Define, Ideate, Prototype and Test—it is most useful to tackle problems that are ill-defined or unknown. With design thinking, teams have the freedom to generate ground-breaking solutions. Your team can get behind hard-to-access insights with SensiML Analytics Toolkit and apply a collection of hands-on methods to help find cutting-edge innovative answers that will ultimately scale for global edge AI applications.
Forest GuardianForest loss as a result of illegal logging is a threat to biodiversity in forest habitats. More and more species are unable to survive as the practice denies the habitat crucial for natural interconnectedness. The extensive fragmentation and degradation of the forest have put more animal and plant species on the verge of extinction. Hence stopping illegal logging would help restore the flora and fauna and restore nature's balance to sustain the world. The solution is to build an illegal logging detection system based on acoustic events at the edge itself powered by solar energy.
The Bird BuddyClimate change is causing birds to migrate earlier each year as the planet warms, meaning they are spending more time in places they didn't used to. Conservation funding to protect endangered migratory birds needs to be adaptive to the changing habitats these birds are now spending more time in. Machine learning at the edge provides an opportunity to study when birds are arriving and where by recognizing their unique bird calls. A distributed network of solar-powered bird call detectors could create a high-resolution dataset of where birds are living and when.
Protect PeatlandsPeatlands are a type of wetlands which are among the most valuable ecosystems on Earth. They are critical for preserving global biodiversity, provide safe drinking water, minimize flood risk and help address climate change. When fire is set or even when peatlands are drying, it releases all the CO2 into atmosphere. Sometimes human set fire intentionally to burn the peatlands to expand farming lands. AI can help to predict when peatlands are drying or set on fire collecting sensor data such as soil moisture level, CO2 emission in the air, increase in temperature and then analyzing these data to predict the situation such as drought, fire etc.
HVAC PerformanceI want to adjust and monitor the performance of my home HVAC system to improve energy efficiency. I have a single HVAC unit in a two story house with a split plenum to divide the airflow between the two levels. I'd like to optimize the air baffle adjustment between the upper and lower floors for the different seasons (heating vs cooling). I'd also like to have a method of monitoring system performance to know when I need filter replacement or other equipment for predictive maintenance.
Illegal Logging DetectorThe environmental effects of illegal logging include deforestation, the loss of biodiversity and the emission of greenhouse gases along with many other factors impacting all life. This system, will be easily reproducible, energy efficient and powerful thanks to the ML algorithms being implemented combined with the cloud services that are used for deployment. With the Infineon IM69D130 PDM digital microphone included in the QuickFeather Development Kit, an audio signal which, through SensiML, we can pass through a neural network will tell us if the noise of a saw is cutting the trees or is a human voice in the forest.
Breeze - Smart Environmental Sensor HubMonitoring of the air quality and other environmental factors is often insufficient in many areas, and this leads to situations when the people and authorities are not aware of the air quality and environmental issues, and thus not action is taken. In this project I will present Breeze the Smart Environmental Sensor Hub, which offers a solution to this problem. Breeze is Sensor Hub capable of collecting data from the connected Sensors. The sensor data is pre-processed, and Machine Learning (ML) are used to extract meaningful information from the models. The Communication Module is used broadcast the sensor data and the ML prediction to a Cloud Backend.
Forest Guardian
Forest loss as a result of illegal logging is a threat to biodiversity in forest habitats. More and more species are unable to survive as the practice denies the habitat crucial for natural interconnectedness. The extensive fragmentation and degradation of the forest have put more animal and plant species on the verge of extinction. Hence stopping illegal logging would help restore the flora and fauna and restore nature's balance to sustain the world. The solution is to build an illegal logging detection system based on acoustic events at the edge itself powered by solar energy.
The Bird Buddy
Climate change is causing birds to migrate earlier each year as the planet warms, meaning they are spending more time in places they didn't used to. Conservation funding to protect endangered migratory birds needs to be adaptive to the changing habitats these birds are now spending more time in. Machine learning at the edge provides an opportunity to study when birds are arriving and where by recognizing their unique bird calls. A distributed network of solar-powered bird call detectors could create a high-resolution dataset of where birds are living and when.
Protect Peatlands
Peatlands are a type of wetlands which are among the most valuable ecosystems on Earth. They are critical for preserving global biodiversity, provide safe drinking water, minimize flood risk and help address climate change. When fire is set or even when peatlands are drying, it releases all the CO2 into atmosphere. Sometimes human set fire intentionally to burn the peatlands to expand farming lands. AI can help to predict when peatlands are drying or set on fire collecting sensor data such as soil moisture level, CO2 emission in the air, increase in temperature and then analyzing these data to predict the situation such as drought, fire etc.
HVAC Performance
I want to adjust and monitor the performance of my home HVAC system to improve energy efficiency. I have a single HVAC unit in a two story house with a split plenum to divide the airflow between the two levels. I'd like to optimize the air baffle adjustment between the upper and lower floors for the different seasons (heating vs cooling). I'd also like to have a method of monitoring system performance to know when I need filter replacement or other equipment for predictive maintenance.
Illegal Logging Detector
The environmental effects of illegal logging include deforestation, the loss of biodiversity and the emission of greenhouse gases along with many other factors impacting all life. This system, will be easily reproducible, energy efficient and powerful thanks to the ML algorithms being implemented combined with the cloud services that are used for deployment. With the Infineon IM69D130 PDM digital microphone included in the QuickFeather Development Kit, an audio signal which, through SensiML, we can pass through a neural network will tell us if the noise of a saw is cutting the trees or is a human voice in the forest.
Breeze - Smart Environmental Sensor Hub
Monitoring of the air quality and other environmental factors is often insufficient in many areas, and this leads to situations when the people and authorities are not aware of the air quality and environmental issues, and thus not action is taken. In this project I will present Breeze the Smart Environmental Sensor Hub, which offers a solution to this problem. Breeze is Sensor Hub capable of collecting data from the connected Sensors. The sensor data is pre-processed, and Machine Learning (ML) are used to extract meaningful information from the models. The Communication Module is used broadcast the sensor data and the ML prediction to a Cloud Backend.
