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Smart HomeIndustrial Automation
WasteWise
AI Smart Trash Can based on nRF52840
Automated waste sorting at the point of disposal using edge AI camera recognition.
Classification Accuracy
94%
Sort Time
1.2 seconds
WasteWise
Client
A sustainability-focused consumer brand creating a smart recycling bin for kitchen use with automated waste categorization.
Challenge
Accurate real-time classification of household waste into recyclable/compost/landfill categories using a low-power MCU, with instantaneous mechanical sorting.
Product Concept & Architecture
The Nordic nRF52840 Cortex-M4F MCU powers the system. An OV2640 camera captures the item when dropped, and three servo-driven bin flaps sort into separate compartments. PIR sensor wakes the system from deep sleep only when in use.
Engineering Solution
We trained a MobileNetV1 SSD model on 15,000 household waste images. The model was INT8 quantized to 380KB and runs entirely on the nRF52840 using TensorFlow Lite Micro. Classification triggers servo rotation within 800ms. A Bluetooth LE companion app provides monthly recycling statistics and tips.
Result
94% correct classification across 30 common waste categories. Power consumption averages 50µA in standby. Users reported 40% reduction in recycling contamination.
Deep Tech FAQ
What makes the AI Smart Trash Can based on nRF52840 unique?+
The AI Smart Trash Can based on nRF52840 leverages custom hardware and edge AI to deliver industry-leading performance and efficiency.
What are the core technical benefits?+
Key benefits include low power consumption, real-time processing, robust connectivity, and a compact form factor tailored for deployment.
Can this architecture be adapted for other use cases?+
Absolutely. The underlying methodology is modular and can be retargeted for various applications with minimal redesign.
Project Profile
Services Delivered
Hardware DesignEmbedded Software
Core Technologies
BLETinyMLRTOS
Silicon & Vendors
NordicOmniVision
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