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| # Table of contents | ||
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| * [Welcome](README.md) | ||
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| ## Image Projects | ||
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| * [Recyclable Materials Sorter - Nvidia Jetson Nano](recyclable-materials-sorter.md) | ||
| * [Analog Meter Reading - Arduino Nicla Vision](analog-meter-reading-with-nicla-vision.md) | ||
| * [Creating Synthetic Data with Nvidia Omniverse Replicator](nvidia-omniverse-replicator.md) | ||
| * [Traffic Monitoring using the Brainchip Akida Neuromorphic Processor](brainchip-akida-traffic-monitoring.md) | ||
| * [Workplace Organizer - Nvidia Jetson Nano](workplace-organizer.md) | ||
| * [Container Counting with a Nicla Vision & FOMO](container-counting-nicla-vision.md) | ||
| * [Smart Smoke Alarm Using Thermal Imaging](smart-smoke-alarm.md) | ||
| * [Shield Bot Autonomous Security Robot](shieldbot.md) | ||
| * [Cyclist Blind Spot Detection](cyclist-blind-spot-detection.md) | ||
| * [IV Drip Fluid-Level Monitoring](iv-drip-fluid-level-monitoring.md) | ||
| * [Worker Safety Monitoring with Nvidia Jetson Nano](worker-safety-monitoring.md) | ||
| * [Delivered Package Detection with Computer Vision](parcel-detection.md) | ||
| * [Bean Leaf Classification with Sony Spresense](bean-leaf-classification.md) | ||
| * [Oil Tank Measurement and Delivery Improvement Using Computer Vision](oil-tank-gauge-monitoring.md) | ||
| * [Adaptable Vision Counters for Smart Industries](adaptable-vision-counters.md) | ||
| * [Smart Cashier with FOMO on a Raspberry Pi](smart-cashier.md) | ||
| * [Identifying PCB Defects with Machine Learning](identifying-pcb-defects.md) | ||
| * [Counting Eggs with Computer Vision](egg-counting-openmv.md) | ||
| * [Elevator Passenger Counting Using Computer Vision](elevator-passenger-counting.md) | ||
| * [Bicycle Counting with a Sony Spresense](spresense-bicycle-counter.md) | ||
| * [ESD Protection using Computer Vision](esd-protection-using-computer-vision.md) | ||
| * [Solar Panel Defect Detection with FOMO on an Arduino Portenta](solar-panel-defect-detection.md) | ||
| * [Automated Label Inspection With FOMO](label-inspection.md) | ||
| * [Knob Eye: Monitor Analog Dials and Knobs with Computer Vision](ml-knob-eye.md) | ||
| * [Posture Detection for Worker Safety](worker-safety-posture-detection.md) | ||
| * [TinyML Digital Counter for Electric Metering System](tinyml-digital-counter-openmv.md) | ||
| * [Corrosion Detection with Seeed reTerminal](corrosion-detection-reterminal.md) | ||
| * [Automated Inventory Management with Computer Vision](automated-inventory-management.md) | ||
| * [Monitoring Retail Checkout Lines with Computer Vision on the RZ/V2L](monitoring-checkout-lines-rzv2l.md) | ||
| * [Smart Grocery Cart Using Computer Vision](smart-grocery-cart-with-computer-vision.md) | ||
| * [Driver Drowsiness Detection With FOMO](driver-drowsiness-detection-with-computer-vision.md) | ||
| * [TinyML for Gastroscopic Image Processing](tinyml-gastroscopic-image-processing.md) | ||
| * [Pharmaceutical Pill Quality Control and Defect Detection](pharmaceutical-pill-defect-detection.md) | ||
| * [Counting Retail Inventory with Computer Vision on the RZ/V2L](counting-retail-inventory-rzv2l.md) | ||
| * [Use Computer Vision on a TI TDA4VM to Deter Shoplifting](deter-shoplifting-with-computer-vision.md) | ||
| * [Retail Image Classification with a Jetson Nano](retail-image-classification-jetson-nano.md) | ||
| * [Smart Factory Prototype with Texas Instruments TDA4VM](smart-factory-with-tda4vm.md) | ||
| * [Fall Detection using Computer Vision for Industrial Workers](worker-fall-detection-computer-vision.md) | ||
| * [Surface Crack Detection and Localization with Texas Instruments TDA4VM](surface-crack-detection-ti-tda4vm.md) | ||
| * [Surface Crack Detection with Seeed reTerminal](surface-crack-detection.md) | ||
| * [The SiLabs xG24 Plus Arducam - Sorting Objects with Computer Vision and Robotics - Part 1](silabs-xg24-card-sorting-and-robotics-1.md) | ||
| * [The SiLabs xG24 Plus Arducam - Sorting Objects with Computer Vision and Robotics - Part 2](silabs-xg24-card-sorting-and-robotics-2.md) | ||
| * [Object Detection and Visualization with the Seeed Studio Grove Vision AI Module](object-detection-ubidots-seeed-grove-ai.md) | ||
| * [Renesas RZ/V2L DRP-AI Pose Detection](renesas-rzv2l-pose-detection.md) | ||
| * [Computer Vision for Product Quality Inspection with Renesas RZ/V2L](renesas-rzv2l-product-quality-inspection.md) | ||
| * [Build a Path-Following, Self-Driving Vehicle Using an Arduino Portenta H7 and Computer Vision](arduino-portenta-h7-self-driving-rc-car.md) | ||
| * [TI TDA4VM - Correct Posture Detection and Enforcement](ti-tda4vm-posture-enforcer.md) | ||
| * [Using a "Bring Your Own Model" Image Classifier for Wound Identification](arduino-portenta-h7-byom-wound-classification.md) | ||
| * [Acute Lymphoblastic Leukemia Classifier](ai-leukemia-classifier.md) | ||
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| ## Audio Projects | ||
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| * [Glass Window Break Detection - Nordic Thingy:53](glass-break-detection-thingy53.md) | ||
| * [Occupancy Sensing - SiLabs EFR32MG24](occupancy-sensing-with-silabs.md) | ||
| * [Smart Appliance Control Using Voice Commands - Nordic Thingy:53](smart-appliance-voice-commands.md) | ||
| * [Illegal Logging Detection - Syntiant TinyML](illegal-logging-detection-syntiant.md) | ||
| * [Illegal Logging Detection - Nordic Thingy:53](illegal-logging-detection-nordic-thingy53.md) | ||
| * [Wearable Cough Sensor and Monitoring](wearable-cough-sensor.md) | ||
| * [Shield Bot Autonomous Security Robot](shieldbot.md) | ||
| * [Collect Data for Keyword Spotting with Raspberry Pi Pico and Edge Impulse](collect-data-raspberrypi-pico.md) | ||
| * [Voice-Activated LED Strip for $10: Raspberry Pi Pico and Edge Impulse](voice-activated-led-controller.md) | ||
| * [Snoring Detection on a Smart Phone](snoring-detection-on-smartphone.md) | ||
| * [Gunshot Audio Classification](gunshot-audio-classification.md) | ||
| * [AI-Powered Patient Assistance](ai-patient-assistance.md) | ||
| * [Acoustic Pipe Leak Detection](acoustic-pipe-leak-detection.md) | ||
| * [Location Identification using Sound](location-sound.md) | ||
| * [Environmental Noise Classification with a Nordic Thingy:53](environmental-noise-classification.md) | ||
| * [Running Faucet Detection with a Seeed XIAO Sense + Blues Cellular](running-faucet-detection.md) | ||
| * [Vandalism Detection via Audio Classification](vandalism-detection-audio-classification.md) | ||
| * [Predictive Maintenance Using Audio Classification](predictive-maintenance-with-sound.md) | ||
| * [Porting an Audio Project from the SiLabs Thunderboard Sense 2 to xG24](audio-recognition-on-silabs-xg24.md) | ||
| * [Environmental Audio Monitoring Wearable with Syntiant TinyML Board](environmental-audio-monitoring-syntiant-tinyml.md) | ||
| * [Environmental Audio Monitoring Wearable with Syntiant TinyML Board - Part 2](environmental-audio-monitoring-syntiant-tinyml-part-2.md) | ||
| * [Keyword Spotting on the Nordic Thingy:53](keyword-spotting-on-nordic-thingy53.md) | ||
| * [Detecting Worker Accidents with Audio Classification](detecting-worker-accidents-with-ai.md) | ||
| * [Snoring Detection with Syntiant NDP120 Neural Decision Processor on Nicla Voice](arduino-nicla-voice-syntiant-snoring-detection.md) | ||
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| ## Predictive Maintenance & Fault Classification | ||
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| * [Predictive Maintenance - Nordic Thingy:91](predictive-maintenance-with-nordic-thingy-91.md) | ||
| * [Brushless DC Motor Anomaly Detection](brushless-dc-motor-anomaly-detection.md) | ||
| * [Industrial Compressor Predictive Maintenance - Nordic Thingy:53](compressor-predictive-maintenance-thingy53.md) | ||
| * [EdenOff: Anticipate Power Outages with Machine Learning](edenoff-anticipate-power-outages.md) | ||
| * [Faulty Lithium-Ion Cell Identification in Battery Packs](faulty-lithium-ion-cell-identification.md) | ||
| * [Acoustic Pipe Leak Detection](acoustic-pipe-leak-detection.md) | ||
| * [Upgrade a Stretch-film Machine: Weight Scale and Predictive Maintenance](stretch-film-machine.md) | ||
| * [Fluid Leak Detection With a Flowmeter and AI](fluid-leak-detection-with-flowmeter-and-ai.md) | ||
| * [Pipeline Clog Detection with a Flowmeter and TinyML](clog-detection-with-ai.md) | ||
| * [Refrigerator Predictive Maintenance](refrigerator-predictive-maintenance.md) | ||
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| ## Accelerometer & Activity Projects | ||
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| * [Arduino x K-Way - Outdoor Activity Tracker](arduino-kway-outdoor-activity-tracker.md) | ||
| * [Arduino x K-Way - Gesture Recognition for Hiking](arduino-kway-gesture-recognition-weather.md) | ||
| * [Arduino x K-Way - TinyML Fall Detection](arduino-kway-fall-detection.md) | ||
| * [Hand Gesture Recognition using TinyML on OpenMV](hand-gesture-recgnition-using-tinyml-on-openmv.md) | ||
| * [Arduin-Row, a TinyML Rowing Machine Coach](arduin-row-tinyml-rowing-machine-coach.md) | ||
| * [Gesture Recognition with a Bangle.js Smartwatch](gesture-recognition-with-banglejs-smartwatch.md) | ||
| * [Bluetooth Fall Detection](bt-fall-detection.md) | ||
| * [Safeguarding Packages During Transit with AI](secure-packages-with-ai.md) | ||
| * [Smart Baby Swing](smart-baby-swing.md) | ||
| * [Warehouse Shipment Monitoring using a Thunderboard Sense 2](warehouse-shipment-monitoring.md) | ||
| * [Patient Communication with Gesture Recognition](patient-gesture-recognition.md) | ||
| * [Hospital Bed Occupancy Detection with TinyML](hospital-bed-occupancy-detection.md) | ||
| * [Fall Detection using a Transformer Model with Arduino Giga R1 WiFi](fall-detection-with-transformers-arduino-giga-r1.md) | ||
| * [Porting a Posture Detection Project from the SiLabs Thunderboard Sense 2 to xG24](silabs-xg24-posture-detection.md) | ||
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| ## Air Quality & Environmental Projects | ||
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| * [Arduino x K-Way - Environmental Asthma Risk Assessment](arduino-kway-environmental-risk-assessment.md) | ||
| * [Gas Detection in the Oil and Gas Industry - Nordic Thingy:91](gas-detection-thingy-91.md) | ||
| * [Smart HVAC System with an Arduino Nicla Vision](arduino-nicla-vision-smart-hvac.md) | ||
| * [Smart HVAC System with a Sony Spresense](sony-spresense-smart-hvac-system.md) | ||
| * [Indoor CO2 Level Estimation Using TinyML](indoor-co2-level-estimation-using-tinyml.md) | ||
| * [Bhopal 84, Detect Harmful Gases](detect-harmful-gases.md) | ||
| * [AI-Assisted Monitoring of Dairy Manufacturing Conditions](dairy-manufacturing-with-ai.md) | ||
| * [Fire Detection Using Sensor Fusion and TinyML](fire-detection-with-arduino-and-tinyml.md) | ||
| * [AI-Assisted Air Quality Monitoring with a DFRobot Firebeetle ESP32](air-quality-monitoring-firebeetle-esp32.md) | ||
| * [Air Quality Monitoring with Sipeed Longan Nano - RISC-V Gigadevice](air-quality-monitoring-sipeed-longan-nano-riscv.md) | ||
| * [Methane Monitoring in Mines - Silabs xG24 Dev Kit](methane-monitoring-silabs-xg24.md) | ||
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| ## Novel Sensor Projects | ||
| * [8x8 ToF Gesture Classification](tof-gesture-classification.md) | ||
| * [Food Irradiation Dose Detection](food-irradiation-detection.md) | ||
| * [Bike Rearview Radar](bike-rearview-radar.md) | ||
| * [Applying EEG Data to Machine Learning, Part 1](eeg-data-machine-learning-part-1.md) | ||
| * [Applying EEG Data to Machine Learning, Part 2](eeg-data-machine-learning-part-2.md) | ||
| * [Applying EEG Data to Machine Learning, Part 3](eeg-data-machine-learning-part-3.md) | ||
| * [Porting a Gesture Recognition Project from the SiLabs Thunderboard Sense 2 to xG24](gesture-recognition-on-silabs-xg24.md) | ||
| * [Fluid Leak Detection With a Flowmeter and AI](fluid-leak-detection-with-flowmeter-and-ai.md) | ||
| * [Pipeline Clog Detection with a Flowmeter and TinyML](clog-detection-with-ai.md) | ||
| * [Liquid Classification with TinyML](liquid-classification-tinyml.md) | ||
| * [AI-Assisted Pipeline Diagnostics and Inspection with mmWave Radar](ai-pipeline-inspection-mmwave.md) | ||
| * [Sensecap A1101 - Soil Quality Detection Using AI and LoRaWAN](sensecap-a1101-lorawan-soil-quality.md) | ||
| * [Smart Diaper Prototype with an Arduino Nicla Sense ME](arduino-nicla-sense-smart-diaper.md) | ||
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| ## Software Integration Demos | ||
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| * [Azure Machine Learning with Kubernetes Compute and Edge Impulse](azure-machine-learning-EI.md) | ||
| * [Community Guide – Using Edge Impulse with Nvidia DeepStream](nvidia-deepstream-community-guide.md) | ||
| * [Creating Synthetic Data with Nvidia Omniverse Replicator](nvidia-omniverse-replicator.md) | ||
| * [NVIDIA Omniverse - Synthetic Data Generation For Edge Impulse Projects](nvidia-omniverse-synthetic-data.md) | ||
| * [ROS2 + Edge Impulse, Part 1: Pub/Sub Node in Python](ros2-part1-pubsub-node.md) | ||
| * [ROS2 + Edge Impulse, Part 2: MicroROS](ros2-part2-microros.md) | ||
| * [Using Hugging Face Datasets in Edge Impulse](using-huggingface-dataset-with-edge-impulse.md) | ||
| * [How to Use a Hugging Face Image Classification Dataset with Edge Impulse](hugging-face-image-classification.md) | ||
| * [Edge Impulse API Usage Sample Application - Jetson Nano Trainer](api-sample-application-jetson-nano.md) | ||
| * [Renesas CK-RA6M5 Cloud Kit - Getting Started with Machine Learning](renesas-ra6m5-getting-started.md) | ||
| * [TI CC1352P Launchpad - Getting Started with Machine Learning](ti-cc1352p-getting-started.md) | ||
| * [MLOps with Edge Impulse and Azure IoT Edge](mlops-azure-iot-edge.md) |
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