Roobonet's starred repositories
SpotMicroAI
SpotMicro AI - How to build a self-learning Robot
robovision
AI and machine leaning-based computer vision for a robot
Smart-Agriculture
This project includes monitoring temperature, humidity and moisture in agricultural field through sensors DHT11, YL69. It will turn ON/OFF motor on the basis of soil moisture and also visualise real time data by using ThingsBoard.
Smart-Agriculture-using-IoT-and-Machine-Learning
The project uses Arduino UNO with multiple sensors attached to it like Soil Moisture sensor, Photoelectric Diode Sensor,Humidity sensor etc that takes reading on a periodic basis.The mission of the project is to intimate the farmers or other stakeholders in predicting when the crop is about to deteriorate. This is accomplished by a Machine Learning Layer that has been modeled to identify the degradation of a crop's health before its degradation starts. It uses KNN-algorithm to cluster the crops according to the impeding eventuality.The next iteration identifies the most probable cause and thorugha UI intimates the stakeholder whta steps needs to be taken to prevent crop-failure
awesome-agriculture
List of project ideas/references which can help engineers build technology for agriculture which can eventually help farmers
Smart-agricultural-system
Smart agricultural system to recommend most profitable crops to farmers
ML-Precision-Agriculture-Web-App
This web application uses Machine Learning to recommend crop, fertilizer, pesticide and storage process based on various variables. Algorithm used is SVM for multi-classification
Agricultural-Price-Prediction-and-Visualization-on-Android-App
In Agriculture Price Monitioring , I have used data provided by open government site data.gov.in, which updates prices of market daily . Working Interface Details: We have provided user choice to see current market prices based on two choices: market wise or commodity wise use increase assesibility options. Market wise: User have to provide State,District and Market name and then select market wise button. Then user will be shown the prices of all the commodities present in the market in graphical format, so that he can analyse the rates on one scale. This feature is mostly helpful for a regular buyer to decide the choice of commodity to buy. He is also given feature to download the data in a tabular format(csv) for accurate analysis. Commodity Wise: User have to provide State,District and Commodity name and then select Commodity wise button. Then user will be shown the prices of all the markets present in the region with the commodity in graphical format, so that he can analyse the cheapest commodity rate. This feature is mostly helpful for wholesale buyers. He is also given feature to download the data in a tabular format(csv) for accurate analysis. On the first activity user is also given forecasting choice. It can be used to forecast the wholesale prices of various commodities at some later year. Regression techniques on timeseries data is used to predict future prices. Select the type of item and click link for future predictions. There are 3 java files Forecasts, DisplayGraphs, DisplayGraphs2 ..... Please change the localhost "server_name" at time of testing as the server name changes each time a new server is made. Things Used: We have used pandas , numpy , scikit learn , seaborn and matplotlib libraries for the same . The dataset is thoroughly analysed using different function available in pandas in my .iPynb file . Not just in-built functions are used but also many user made functions are made to make the working smooth . Various graphs like pointplot , heat-map , barplot , kdeplot , distplot, pairplot , stripplot , jointplot, regplot , etc are made and also deployed on the android app as well . To integrate the android app and machine learning analysis outputs , we have used Flask to host our laptop as the server . We have a separate file for the Flask as server.py . Where all the the necessary stuff of clint request and server response have been dealt with . We have used npm package ngrok for tunneling purpose and hosting . A different .iPynb file is used for the time series predictions using regression algorithms and would send the csv file of prediction along with the graph to the andoid app when given a request .
Matrix16x8
Arduino Matrix 16x8 using MCU MAX7219 module
IOT-Project_AgriCloud
IOT based project that provides live monitoring of climatic conditions and better irrigation.
Arduino-74HC595-LED-Matrix
Basic LED matrix library for an Arduino with a 74HC595 shift register.
TDT4290_Aqueous
Aqueous, a desktop application used for controlling ROVs at fish farms
Smart-Aquaculture-Monitoring-and-Control-using-WSN-and-CAN
Analyzing the water conditions and take proper action in aqua culture plays a vital role for getting better yield.In this project water quality is monitored using ph, DO,Ambient light and temperature sensor interface to an AVR controller along with aerator motor control.The water level in the pond is constantly monitored and the inflow motor is controlled based on the set threshold values. These two modules communicate using RF and CAN respectively, following displaying data on TFT of LPC 1768 board.
agri-erpnext
A set of agriculture modules for erpnext
lichtkrant
Arduino ESP8266 software for driving a 80x7 pixel red/green/amber moving LED sign
ips_html_form_builder
Form Builder module for odoo 13
bridge-builder
Bridgebuilder does provide a set of tools to create oddo, flectra, cubicerp and similar odoo based erp systems