Here are some of my projects. You can see more here.
All Apps are free and open source.
Kostal Smart Power Meter Viewer
Kostal Smart Metter ticker to check the Power origin and the quantity.
BioNlpOcr
An Android 4 Application that recognizes text.
MoveMouse
A MacOS application that moves the mouse.
Podcast Audio Clipper
Transcribes podcasts and extracts key-topic clips seamlessly.
BTCSenseHat
Python script to check BTC / USD last price and show it on a raspberry pi Sense Hat.
Wifi Password Reminder
WPR is an app that shows the passwords for wifi connections which have connected .
Keiser.M3i.BLE-HCI-Simulator
Simulates an M3i trainer.
TFMIOT
Deep Learning in IoT. Convolutional neural networks with Images aplied to anautonomous vehicule.
Time and Space
Puzzle game made with c and lua
Android Play Store
Profile with all the apps published
Kostal Smart Power Meter Viewer
If you have a Kostal Smart Metter, you can have a ticket to check the Power origin and the quantity of ha Kostal Smart meter. Normally this is used when you have a solar power supply and the energy net power supply. If the installation is using the energy net power supply it will be shown as color red and an amount of points from 0 to max_power value. If the power comes from the solar pannels it will be shown on green.
Biomedical concept searcher Android App for Gyngerbread. Based in tess-two, Leptonica and Mezzofanti projects. This project has developed a tool to be used in mobile devices, which shows additional information to the user in real time, about biomedical concepts, from a mobile picture with the biomedical text.
Movemouse is a MacOS Application that moves the mouse based on Vorce/Jerry project. It uses CGEvent that defines an opaque type that represents a low-level hardware event. It ofers a simple interface to randomly move the mouse across the screen.
Movemouse is MacOS 11.4 Big Sur or later compatible.
Demo video
In the next video you can see a demo of how it works.
PodcastAudioClipper is a powerful tool encapsulated in a Jupyter Notebook that takes audio podcasts, transcribes them to text using Wisper, and extracts key topic segments into individual audio clips of up to 5 minutes. The clips are titled based on the key topics identified within the segment, making it a breeze to sort through and share the highlights of your favorite podcasts.
WPR is an app that shows the passwords for wifi connections which have connected .
WPR is an app that shows the passwords for wifi connections which have connected .
Show all information system wifi connections you have configured on your device
Share passwords wifi connections via scanning the QR code .
You can see the password of the wifi connections You have in your Android
The purpose of this application is not hack wifi connections.
For some terminal you need to be root.
*This app does not provide the password of wifi connections if not previously provided . No wifi networks pirates . There is no security audit wifi connections .
What terminals work?
*Some terminals with certain versions show the password without having to be root ( need feedback !)
*HTC desire HD FROYO version (Gingerbread need not)
*Rooted Terminals.
BUG : In Android 4.3+ google has changed the wifi password encryption, and It’s not actually working.
Its a known issue. We are working on it.
Simulates an M3i trainer. Simulator uses a Linux Bash script which requires an HCI BLE device to operate.
Simulates an M3i for development and testing purposes.
Simulator uses a Linux Bash script which requires an HCI BLE device to operate.
If no HCI BLE device is available, we recommend connecting a USB adapter with Linux compatibility.
Recommended USB Adapter: Plugable USB Adapter on Amazon US
This script is very basic, and designed to be a building block for testing and development. If you develop a more advanced script and would like to share it with other developers, please send a pull request and we will be happy to bring it into the repository
Use
Ensure that BlueZ library is installed.
sudo apt-get install bluez
Run script with root permissions. (hciconfig requires root permission on most distros)
Aprendizaje profundo en IoT. Redes neuronales convolucionales con imágenes aplicadas a un vehículo autónomo.Deep Learning in IoT. Convolutional neural networks with Images aplied to an autonomous vehicule.
En el presente trabajo se realiza un estudio, desarrollo y mejora de un vehículo autóno- mo de bajo coste usando una cámara y aprendizaje profundo. El vehículo aprenderá de un método de conducción autónoma usando OpenCV. Al mismo tiempo se le hace reaccionar a diferentes señales y eventos que pueda encontrar a su paso.