From 85f81691be44fac59f29ae08c89e25175d08e18d Mon Sep 17 00:00:00 2001 From: david Date: Wed, 13 Sep 2023 10:41:04 -0700 Subject: [PATCH] description update --- .../arduino-kway-fall-detection.md | 2 +- .../arduino-kway-gesture-recognition-weather.md | 2 +- .../hospital-bed-occupancy-detection-arduino-nano-33.md | 2 +- audio-projects/glass-break-detection-nordic-thingy53.md | 2 +- .../smart-appliance-voice-commands-nordic-thingy53.md | 2 +- audio-projects/wearable-cough-sensor-arduino-nano-33.md | 2 +- image-projects/nvidia-omniverse-replicator.md | 2 +- .../brushless-dc-motor-anomaly-detection.md | 2 +- software-integration-demos/mlops-azure-iot-edge.md | 5 +++++ software-integration-demos/ros2-part1-pubsub-node.md | 8 +++----- 10 files changed, 16 insertions(+), 13 deletions(-) diff --git a/accelerometer-and-activity-projects/arduino-kway-fall-detection.md b/accelerometer-and-activity-projects/arduino-kway-fall-detection.md index dfb34017..5c8c574d 100644 --- a/accelerometer-and-activity-projects/arduino-kway-fall-detection.md +++ b/accelerometer-and-activity-projects/arduino-kway-fall-detection.md @@ -1,7 +1,7 @@ --- description: >- Train a TinyML model to detect the motion of falling down, then connect via - Bluetooth to make an emergency call + Bluetooth to make an emergency call. --- # Arduino x K-Way - TinyML Fall Detection diff --git a/accelerometer-and-activity-projects/arduino-kway-gesture-recognition-weather.md b/accelerometer-and-activity-projects/arduino-kway-gesture-recognition-weather.md index 5278edd6..9ca198c7 100644 --- a/accelerometer-and-activity-projects/arduino-kway-gesture-recognition-weather.md +++ b/accelerometer-and-activity-projects/arduino-kway-gesture-recognition-weather.md @@ -1,7 +1,7 @@ --- description: >- Use a Nicla Sense ME attached to the sleeve of a K-way jacket for gesture - recognition and bad weather prediction + recognition and bad weather prediction. --- # Arduino x K-Way - Gesture Recognition for Hiking diff --git a/accelerometer-and-activity-projects/hospital-bed-occupancy-detection-arduino-nano-33.md b/accelerometer-and-activity-projects/hospital-bed-occupancy-detection-arduino-nano-33.md index 855f52be..40506e22 100644 --- a/accelerometer-and-activity-projects/hospital-bed-occupancy-detection-arduino-nano-33.md +++ b/accelerometer-and-activity-projects/hospital-bed-occupancy-detection-arduino-nano-33.md @@ -4,7 +4,7 @@ description: >- hospitals or care facilities. --- -# Hospital Bed Occupancy Detetction with TinyML +# Hospital Bed Occupancy Detection with TinyML Created By: [Adam Milton-Barker](https://www.adammiltonbarker.com/) diff --git a/audio-projects/glass-break-detection-nordic-thingy53.md b/audio-projects/glass-break-detection-nordic-thingy53.md index ba710fcb..5d65a646 100644 --- a/audio-projects/glass-break-detection-nordic-thingy53.md +++ b/audio-projects/glass-break-detection-nordic-thingy53.md @@ -1,6 +1,6 @@ --- description: >- - Build a machine learning model and deploy it to a Nordic Semi Thingy:53 to + Build a machine learning model and deploy it to a Nordic Thingy:53 to detect the sound of breaking glass. --- diff --git a/audio-projects/smart-appliance-voice-commands-nordic-thingy53.md b/audio-projects/smart-appliance-voice-commands-nordic-thingy53.md index 86dbaf1f..d1aff74d 100644 --- a/audio-projects/smart-appliance-voice-commands-nordic-thingy53.md +++ b/audio-projects/smart-appliance-voice-commands-nordic-thingy53.md @@ -1,6 +1,6 @@ --- description: >- - Using a Nordic Semi Thingy:53 with Keyword Spotting to turn an ordinary device + Using a Nordic Thingy:53 with Keyword Spotting to turn an ordinary device into a smart appliance. --- diff --git a/audio-projects/wearable-cough-sensor-arduino-nano-33.md b/audio-projects/wearable-cough-sensor-arduino-nano-33.md index 00b624b3..2e6afea1 100644 --- a/audio-projects/wearable-cough-sensor-arduino-nano-33.md +++ b/audio-projects/wearable-cough-sensor-arduino-nano-33.md @@ -1,6 +1,6 @@ --- description: >- - An exploration into using Machine Learning to better monitor a patient + An exploration into using machine learning to better monitor a patient coughing, to improve medical outcomes. --- diff --git a/image-projects/nvidia-omniverse-replicator.md b/image-projects/nvidia-omniverse-replicator.md index fde459f0..0eae5930 100644 --- a/image-projects/nvidia-omniverse-replicator.md +++ b/image-projects/nvidia-omniverse-replicator.md @@ -1,7 +1,7 @@ --- description: >- Learn how to generate photorealistic images in Nvidia Omniverse Replicator and - build an object detection model using Edge Impulse + build an object detection model using Edge Impulse. --- # Creating Synthetic Data with Nvidia Omniverse Replicator diff --git a/predictive-maintenance-and-fault-classification/brushless-dc-motor-anomaly-detection.md b/predictive-maintenance-and-fault-classification/brushless-dc-motor-anomaly-detection.md index 2e539ea7..351a1002 100644 --- a/predictive-maintenance-and-fault-classification/brushless-dc-motor-anomaly-detection.md +++ b/predictive-maintenance-and-fault-classification/brushless-dc-motor-anomaly-detection.md @@ -131,7 +131,7 @@ Now we're ready to apply the signal processing to our data. In the "**Generate f We're ready to move on to the next block where we create our machine learning model. We're almost done! Once we've generated the DSP features we can navigate to the next screen "Anomaly detection" from the menu on the left. -On this screen we can set the number ofclusters, as well as select the axes according to which our data will be clustered. For this example all axes were selected, but if you know that certain axes are more / less important it's best to select them accordingly _(this can be determined by using samples where the motor is experiencing faulty behavior and using the_ _**Calculate feature importance**_ \_option in the Generate features section. More on this [here](https://www.edgeimpulse.com/blog/advanced-anomaly-detection-with-feature-importance).) +On this screen we can set the number of clusters, as well as select the axes according to which our data will be clustered. For this example all axes were selected, but if you know that certain axes are more / less important it's best to select them accordingly _(this can be determined by using samples where the motor is experiencing faulty behavior and using the_ _**Calculate feature importance**_ \_option in the Generate features section. More on this [here](https://www.edgeimpulse.com/blog/advanced-anomaly-detection-with-feature-importance).) ![](https://hackster.imgix.net/uploads/attachments/1444526/image\_iPSTpWYYod.png?auto=compress,format\&w=740\&h=555\&fit=max) diff --git a/software-integration-demos/mlops-azure-iot-edge.md b/software-integration-demos/mlops-azure-iot-edge.md index 17430e5a..452779db 100644 --- a/software-integration-demos/mlops-azure-iot-edge.md +++ b/software-integration-demos/mlops-azure-iot-edge.md @@ -1,3 +1,8 @@ +--- +description: >- + Use Docker containers distributed via Azure IoT Edge to build and deploy machine leaning models in an MLOps loop. +--- + # MLOps with Edge Impulse and Azure IoT Edge Created By: David Tischler diff --git a/software-integration-demos/ros2-part1-pubsub-node.md b/software-integration-demos/ros2-part1-pubsub-node.md index 7017c379..4305cb46 100644 --- a/software-integration-demos/ros2-part1-pubsub-node.md +++ b/software-integration-demos/ros2-part1-pubsub-node.md @@ -1,8 +1,6 @@ --- description: >- - In this tutorial we’ll look at how to build an AI-driven ROS2 node using an - Edge Impulse model. This tutorial is “sensor agnostic”, but a 3-axis - accelerometer is used for demonstration. + Build an AI-driven ROS2 node for robotics using an Edge Impulse model and a 3-axis accelerometer. --- # ROS2 + Edge Impulse, Part 1: Pub/Sub Node in Python @@ -11,9 +9,9 @@ Created By: Avi Brown Public Project Link: [https://studio.edgeimpulse.com/public/108508/latest](https://studio.edgeimpulse.com/public/108508/latest) -{% embed url="https://www.youtube.com/watch?v=0SabLvJqSaM" %} +GitHub Repository: [https://github.com/avielbr/edge-impulse/tree/main/ros2/ei\_ros2](https://github.com/avielbr/edge-impulse/tree/main/ros2/ei\_ros2) -### Full code for this project can be [found here](https://github.com/avielbr/edge-impulse/tree/main/ros2/ei\_ros2) +{% embed url="https://www.youtube.com/watch?v=0SabLvJqSaM" %} ### Background