🎛 Machine Learning Based Gesture Detection Watch (ESP8266)
We’ll be taking the watch built in the previous instructable and plunge in some Machine Learning and see if we can detect what kind of gesture we are performing, and maybe in upcoming instructable we can use this gesture to perform some very cool projects based on this.
Final result:
Once the code is uploaded successfully make any gesture, the oled display should say what gesture you are performing. In my case the model worked 95% of the time, it just sometimes it suffers to find the right swipe gesture. Probably, the data I collected was noisy or maybe I wasn’t doing the motion right while collecting the data. Anyhow 95% is still good for me, we can do so much with this gesture detection!
More information...
#projects #machine_learning
We’ll be taking the watch built in the previous instructable and plunge in some Machine Learning and see if we can detect what kind of gesture we are performing, and maybe in upcoming instructable we can use this gesture to perform some very cool projects based on this.
Final result:
Once the code is uploaded successfully make any gesture, the oled display should say what gesture you are performing. In my case the model worked 95% of the time, it just sometimes it suffers to find the right swipe gesture. Probably, the data I collected was noisy or maybe I wasn’t doing the motion right while collecting the data. Anyhow 95% is still good for me, we can do so much with this gesture detection!
More information...
#projects #machine_learning
👍2
🎛 Smart Video Doorbell: Intercom on Raspberry Pi
I came across some nice software to make a fast video / 2-way audio doorbell with a Raspberry Pi, and found a way to fit all the components in a small case. I will show you how to build it, including how to make push notifications work when you press the button.
More information...
#projects #raspberry #IoT
I came across some nice software to make a fast video / 2-way audio doorbell with a Raspberry Pi, and found a way to fit all the components in a small case. I will show you how to build it, including how to make push notifications work when you press the button.
More information...
#projects #raspberry #IoT
👍1
📰 Alternatives to Raspberry Pi in 2021:
▫️Hackboard 2 is a new single-board computer designed from the ground up to be one of the most powerful and affordable Windows-capable, Intel-based computers ever. With optional 4G or 5G connectivity, it is ideal for students, teachers, families, makers, and hobbyists alike. Unlike the Raspberry Pi, Hackboard 2 is based on a powerful Intel processor capable of running Windows.
▫️ZimaBoard is a low-cost single board server designed for makers and geeks. Zimaboard has both the expandability of an x86 SBC, and the appropriate power of a micro server. With ZimaBoard, you can setup a 4 Terabyte personal cloud in 5 minutes, configure a secure VPN to protect your digital footprint, tune your network with OpenWrt and pfSense, build a 4K media server that runs with Plex, share and collaborate with team members on your files, or upgrade your smart projects across different systems.
▫️ROCK Pi 4 is a Single Board Computer in an ultra-small form factor that offers class-leading performance while leveraging outstanding mechanical compatibility. The ROCK Pi 4 offers makers, IoT enthusiasts, hobbyists, PC DIY enthusiasts and others a reliable and extremely capable platform for building and tinkering their ideas into reality.
▫️ODROID-H2+ features an Intel Celeron J4115 Gemini Lake processor, two SO-DIMM slots for memory, two SATA ports and M.2 NVMe slot for storage, two Gigabit Ethernet ports, a mix of USB 3.0 and 2.0 ports, and more. This very powerful x86 64bit single board computer has large memory capacity and advanced IO ports.
▫️The NanoPi R4S (as "R4S") is an open source platform with dual-Gbps Ethernet ports designed and developed by FriendlyElec for IoT applications. The NanoPi R4S uses the RK3399 SoC. It has two Gbps Ethernet ports and 1G/4G DDR4 RAM. FriendlyElec ported an OpenWrt system for it. It works with Docker CE. It is a good platform for developing IoT applications, NAS applications, smart home gateways etc.
▫️The NVIDIA® Jetson Nano™ 2GB Developer Kit is ideal for learning, building, and teaching AI and robotics—built for creators and priced for everyone. The Jetson Nano 2GB Developer Kit delivers incredible AI performance at a low price. It makes the world of AI and robotics accessible to everyone with the exact same software and tools used to create breakthrough AI products across all industries.
▫️ASUS Tinker Board is a Single Board Computer in an ultra-small form factor that offers class-leading performance while leveraging outstanding mechanical compatibility. The Tinker Board offers makers, IoT enthusiasts, hobbyists, PC DIY enthusiasts and others a reliable and extremely capable platform for building and tinkering their ideas into reality.
#news #boards #raspberry #hardware #jetson_nano
▫️Hackboard 2 is a new single-board computer designed from the ground up to be one of the most powerful and affordable Windows-capable, Intel-based computers ever. With optional 4G or 5G connectivity, it is ideal for students, teachers, families, makers, and hobbyists alike. Unlike the Raspberry Pi, Hackboard 2 is based on a powerful Intel processor capable of running Windows.
▫️ZimaBoard is a low-cost single board server designed for makers and geeks. Zimaboard has both the expandability of an x86 SBC, and the appropriate power of a micro server. With ZimaBoard, you can setup a 4 Terabyte personal cloud in 5 minutes, configure a secure VPN to protect your digital footprint, tune your network with OpenWrt and pfSense, build a 4K media server that runs with Plex, share and collaborate with team members on your files, or upgrade your smart projects across different systems.
▫️ROCK Pi 4 is a Single Board Computer in an ultra-small form factor that offers class-leading performance while leveraging outstanding mechanical compatibility. The ROCK Pi 4 offers makers, IoT enthusiasts, hobbyists, PC DIY enthusiasts and others a reliable and extremely capable platform for building and tinkering their ideas into reality.
▫️ODROID-H2+ features an Intel Celeron J4115 Gemini Lake processor, two SO-DIMM slots for memory, two SATA ports and M.2 NVMe slot for storage, two Gigabit Ethernet ports, a mix of USB 3.0 and 2.0 ports, and more. This very powerful x86 64bit single board computer has large memory capacity and advanced IO ports.
▫️The NanoPi R4S (as "R4S") is an open source platform with dual-Gbps Ethernet ports designed and developed by FriendlyElec for IoT applications. The NanoPi R4S uses the RK3399 SoC. It has two Gbps Ethernet ports and 1G/4G DDR4 RAM. FriendlyElec ported an OpenWrt system for it. It works with Docker CE. It is a good platform for developing IoT applications, NAS applications, smart home gateways etc.
▫️The NVIDIA® Jetson Nano™ 2GB Developer Kit is ideal for learning, building, and teaching AI and robotics—built for creators and priced for everyone. The Jetson Nano 2GB Developer Kit delivers incredible AI performance at a low price. It makes the world of AI and robotics accessible to everyone with the exact same software and tools used to create breakthrough AI products across all industries.
▫️ASUS Tinker Board is a Single Board Computer in an ultra-small form factor that offers class-leading performance while leveraging outstanding mechanical compatibility. The Tinker Board offers makers, IoT enthusiasts, hobbyists, PC DIY enthusiasts and others a reliable and extremely capable platform for building and tinkering their ideas into reality.
#news #boards #raspberry #hardware #jetson_nano
📟 Creating a Text-to-speech engine with Google Tesseract and Arm NN on Raspberry Pi
A text-to-speech (TTS) engine is the crucial element of systems looking to create a natural interaction between humans and machines based on embedded devices. An embedded device can, for example, help visually impaired people read signs, letters, and documents. More specifically, a device can use optical character recognition to let a user know what it sees in an image.
In this article, you will learn how to do so with TensorFlow, OpenCV, Festival, and a Raspberry Pi. I will use the TensorFlow machine learning platform along with a pre-trained Keras-OCR model to perform OCR. OpenCV will be used to capture images from the web camera. Finally, the Festival speech synthesis system will serve as the TTS module. Everything will then be combined to build the Python app for Raspberry Pi.
More information...
#projects #raspberry #machine_learning #artificial_intelligence #python
A text-to-speech (TTS) engine is the crucial element of systems looking to create a natural interaction between humans and machines based on embedded devices. An embedded device can, for example, help visually impaired people read signs, letters, and documents. More specifically, a device can use optical character recognition to let a user know what it sees in an image.
In this article, you will learn how to do so with TensorFlow, OpenCV, Festival, and a Raspberry Pi. I will use the TensorFlow machine learning platform along with a pre-trained Keras-OCR model to perform OCR. OpenCV will be used to capture images from the web camera. Finally, the Festival speech synthesis system will serve as the TTS module. Everything will then be combined to build the Python app for Raspberry Pi.
More information...
#projects #raspberry #machine_learning #artificial_intelligence #python
🎛 Dog Mood Detector with Google Cloud and Raspberry Pi
In this article we’re going to explore the idea of a dog mood detector. We’ll build a device that listens to the ambient sound around it and, if a dog is present, attempts to determine which type of sound the dog is making: a friendly bark, a scared whimper, or an aggressive growl.
Based on the preferences of the user, the device vibrates when it thinks they should check on their dog. This could be used, perhaps, to help owners keep tabs on their dog when they're out of earshot. To prototype this device, we’ll use a Raspberry Pi, which is my go-to platform for implementing Machine Learning on edge devices.
More information...
#projects #raspberry #machine_learning #IoT #python
In this article we’re going to explore the idea of a dog mood detector. We’ll build a device that listens to the ambient sound around it and, if a dog is present, attempts to determine which type of sound the dog is making: a friendly bark, a scared whimper, or an aggressive growl.
Based on the preferences of the user, the device vibrates when it thinks they should check on their dog. This could be used, perhaps, to help owners keep tabs on their dog when they're out of earshot. To prototype this device, we’ll use a Raspberry Pi, which is my go-to platform for implementing Machine Learning on edge devices.
More information...
#projects #raspberry #machine_learning #IoT #python
📟 Automatic Trash Classification with Raspberry Pi and Arm NN Machine Learning
AI is now moving to edge devices. Arm is leading this revolution by providing accelerated hardware IPs and middle-layer solutions.
In practice, this means you can train your models using the most popular ML frameworks. You can then load models and optimize them on your edge device to perform fast inference, eliminating network and privacy problems.
To demonstrate ML with edge computing resources, we'll use Arm NN APIs to classify images of trash from a webcam attached to a Raspberry Pi. The Raspberry Pi will display classification results.
More information...
#projects #raspberry #artificial_intelligence #machine_learning
AI is now moving to edge devices. Arm is leading this revolution by providing accelerated hardware IPs and middle-layer solutions.
In practice, this means you can train your models using the most popular ML frameworks. You can then load models and optimize them on your edge device to perform fast inference, eliminating network and privacy problems.
To demonstrate ML with edge computing resources, we'll use Arm NN APIs to classify images of trash from a webcam attached to a Raspberry Pi. The Raspberry Pi will display classification results.
More information...
#projects #raspberry #artificial_intelligence #machine_learning
🎚 OSHChip (OpenSourceHardwareChip)
The most striking thing you see is that it is the size of a 16 pin DIP, and unlike other processor boards, it is designed from the start to be compatible with the white breadboards that are commonly used by electronic hobbyists, robotics projects, and oh so many hackaday projects.
Unlike other processor boards that are far larger, OSHChip can be plugged into the middle two rows of a bread board, and it doesn’t cover the connected holes that you will be connecting to.
Specifications:
▫️ ARM
▫️ 2.4 GHz Bluetooth Low Energy radio
▫️ Broad range of built-in Peripheral functions
▫️ 256 KBytes of Flash memory for program and data
▫️ 32 KBytes of SRAM
▫️ Support for in-system debugging including breakpoints
More information...
#boards #cortex
The most striking thing you see is that it is the size of a 16 pin DIP, and unlike other processor boards, it is designed from the start to be compatible with the white breadboards that are commonly used by electronic hobbyists, robotics projects, and oh so many hackaday projects.
Unlike other processor boards that are far larger, OSHChip can be plugged into the middle two rows of a bread board, and it doesn’t cover the connected holes that you will be connecting to.
Specifications:
▫️ ARM
Cortex-M0 32 bit (16 MHz)▫️ 2.4 GHz Bluetooth Low Energy radio
▫️ Broad range of built-in Peripheral functions
▫️ 256 KBytes of Flash memory for program and data
▫️ 32 KBytes of SRAM
▫️ Support for in-system debugging including breakpoints
More information...
#boards #cortex