Farmatica

Farmatica - Intelligent Agricultural System

Farmatica is an advanced agricultural system powered by state-of-the-art AI (Artificial Intelligence) and ML (Machine Learning) technologies. It is designed to revolutionize farming practices and enhance agricultural productivity through data-driven insights and automation.

Overview

Farmatica leverages cutting-edge AI and ML algorithms to provide farmers with real-time data analysis and predictive capabilities. By analyzing various factors such as weather conditions, soil moisture, crop health, and historical data, Farmatica helps farmers make informed decisions about crop management, leading to optimized yields and improved resource utilization.

Key Features

Real-time Monitoring: Farmatica continuously collects data from various sensors and sources, allowing farmers to monitor their fields in real-time. This includes information on temperature, humidity, soil moisture, and more.
Intelligent Analytics: Through advanced AI algorithms, Farmatica analyzes the collected data to gain insights into crop health, identify potential issues, and predict optimal timing for irrigation, fertilization, and pest control measures.
Automated Decision-Making: Farmatica provides actionable recommendations to farmers based on the analyzed data and predictive models. These recommendations help farmers optimize their farming practices, resulting in improved yields and reduced resource waste.
Remote Control: With Farmatica, farmers can remotely control and adjust various parameters in their fields, such as irrigation systems, fertilization schedules, and pest control mechanisms. This allows for efficient and timely interventions without the need for physical presence.
Data Integration: Farmatica seamlessly integrates with existing farming systems and data sources, such as weather stations and soil analysis tools. This ensures comprehensive data collection and a holistic view of the farm’s operations.
Scalability and Customization: Farmatica is designed to be scalable and adaptable to different farm sizes and types of crops. The system can be customized to meet specific farming requirements, enabling farmers to tailor it to their unique needs.

Getting Started

To start using Farmatica, follow these steps:

Hardware Setup: Install the necessary sensors and IoT devices in your fields, such as temperature and humidity sensors, soil moisture meters, and weather stations. Connect these devices to the Farmatica hub.
Data Integration: Configure Farmatica to integrate with your existing data sources, such as weather APIs and soil analysis tools. This ensures comprehensive data collection and accurate analysis.
Machine Learning Model Training: Train the ML models within Farmatica using historical data from your farm. This step helps the system learn patterns and make accurate predictions specific to your farm’s conditions.
Dashboard and Control: Access the Farmatica dashboard, either through a web interface or a mobile application. The dashboard provides real-time insights, recommendations, and control options for your farming operations.

Requirements

Farmatica Hub: The central device that collects and processes data from sensors and controls farm systems.
IoT Sensors: Temperature, humidity, soil moisture, and other relevant sensors for collecting field data.
Internet connectivity: Required for data transmission and remote access to the Farmatica system.
Web Browser or Mobile App: Access the Farmatica dashboard and control interface through a supported web browser or mobile application.

Support and Feedback

For any questions, issues, or feedback regarding Farmatica, please contact our support team at support@farmatica.com. We are committed to providing timely assistance and continuously improving the system based on user input.

Conclusion

Farmatica represents the future of agriculture, where advanced AI and ML technologies empower farmers to make data-driven decisions and optimize their farming practices. By leveraging real-time data analysis, predictive algorithms, and remote control capabilities, Farmatica aims to revolutionize the agricultural industry and contribute to sustainable and efficient food production.

Project Structure

Node is required for generation and recommended for development. package.json is always generated for a better development experience with prettier, commit hooks, scripts and so on.

In the project root, JHipster generates configuration files for tools like git, prettier, eslint, husky, and others that are well known and you can find references in the web.

/src/* structure follows default Java structure.

.yo-rc.json - Yeoman configuration file JHipster configuration is stored in this file at generator-jhipster key. You may find generator-jhipster-* for specific blueprints configuration.
.yo-resolve (optional) - Yeoman conflict resolver Allows to use a specific action when conflicts are found skipping prompts for files that matches a pattern. Each line should match [pattern] [action] with pattern been a Minimatch pattern and action been one of skip (default if ommited) or force. Lines starting with # are considered comments and are ignored.
.jhipster/*.json - JHipster entity configuration files
npmw - wrapper to use locally installed npm. JHipster installs Node and npm locally using the build tool by default. This wrapper makes sure npm is installed locally and uses it avoiding some differences different versions can cause. By using ./npmw instead of the traditional npm you can configure a Node-less environment to develop or test your application.
/src/main/docker - Docker configurations for the application and services that the application depends on

Development

Before you can build this project, you must install and configure the following dependencies on your machine:

Node.js: We use Node to run a development web server and build the project. Depending on your system, you can install Node either from source or as a pre-packaged bundle.

After installing Node, you should be able to run the following command to install development tools. You will only need to run this command when dependencies change in package.json.

npm install

We use npm scripts and Angular CLI with Webpack as our build system.

If you are using hazelcast as a cache, you will have to launch a cache server. To start your cache server, run:

docker compose -f src/main/docker/hazelcast-management-center.yml up -d

Run the following commands in two separate terminals to create a blissful development experience where your browser auto-refreshes when files change on your hard drive.

./mvnw
npm start

Npm is also used to manage CSS and JavaScript dependencies used in this application. You can upgrade dependencies by specifying a newer version in package.json. You can also run npm update and npm install to manage dependencies. Add the help flag on any command to see how you can use it. For example, npm help update.

The npm run command will list all of the scripts available to run for this project.

PWA Support

JHipster ships with PWA (Progressive Web App) support, and it’s turned off by default. One of the main components of a PWA is a service worker.

The service worker initialization code is disabled by default. To enable it, uncomment the following code in src/main/webapp/app/app.module.ts:

ServiceWorkerModule.register('ngsw-worker.js', { enabled: false }),

Managing dependencies

For example, to add Leaflet library as a runtime dependency of your application, you would run following command:

npm install --save --save-exact leaflet

To benefit from TypeScript type definitions from DefinitelyTyped repository in development, you would run following command:

npm install --save-dev --save-exact @types/leaflet

Then you would import the JS and CSS files specified in library’s installation instructions so that Webpack knows about them: Edit src/main/webapp/app/app.module.ts file:

import 'leaflet/dist/leaflet.js';

Edit src/main/webapp/content/scss/vendor.scss file:

@import 'leaflet/dist/leaflet.css';

Note: There are still a few other things remaining to do for Leaflet that we won’t detail here.

For further instructions on how to develop with JHipster, have a look at Using JHipster in development.

Developing Microfrontend

Microservices doesn’t contain every required backend feature to allow microfrontends to run alone. You must start a pre-built gateway version or from source.

Start gateway from source:

cd gateway
npm run docker:db:up # start database if necessary
npm run docker:others:up # start service discovery and authentication service if necessary
npm run app:start # alias for ./(mvnw|gradlew)

Microfrontend’s build-watch script is configured to watch and compile microfrontend’s sources and synchronizes with gateway’s frontend. Start it using:

cd microfrontend
npm run docker:db:up # start database if necessary
npm run build-watch

It’s possible to run microfrontend’s frontend standalone using:

cd microfrontend
npm run docker:db:up # start database if necessary
npm watch # alias for `npm start` and `npm run backend:start` in parallel

Using Angular CLI

You can also use Angular CLI to generate some custom client code.

For example, the following command:

ng generate component my-component

will generate few files:

create src/main/webapp/app/my-component/my-component.component.html
create src/main/webapp/app/my-component/my-component.component.ts
update src/main/webapp/app/app.module.ts

JHipster Control Center

JHipster Control Center can help you manage and control your application(s). You can start a local control center server (accessible on http://localhost:7419) with:

docker compose -f src/main/docker/jhipster-control-center.yml up

Doing API-First development using openapi-generator-cli

OpenAPI-Generator is configured for this application. You can generate API code from the src/main/resources/swagger/api.yml definition file by running:

./mvnw generate-sources

Then implements the generated delegate classes with @Service classes.

To edit the api.yml definition file, you can use a tool such as Swagger-Editor. Start a local instance of the swagger-editor using docker by running: docker compose -f src/main/docker/swagger-editor.yml up -d. The editor will then be reachable at http://localhost:7742.

Refer to Doing API-First development for more details.

Building for production

Packaging as jar

To build the final jar and optimize the Farmatica application for production, run:

./mvnw -Pprod clean verify

This will concatenate and minify the client CSS and JavaScript files. It will also modify index.html so it references these new files. To ensure everything worked, run:

java -jar target/*.jar

Then navigate to http://localhost:8081 in your browser.

Refer to Using JHipster in production for more details.

Packaging as war

To package your application as a war in order to deploy it to an application server, run:

./mvnw -Pprod,war clean verify

Testing

To launch your application’s tests, run:

./mvnw verify

Client tests

Unit tests are run by Jest. They’re located in src/test/javascript/ and can be run with:

npm test

Other tests

Performance tests are run by Gatling and written in Scala. They’re located in src/test/java/gatling/simulations.

You can execute all Gatling tests with

./mvnw gatling:test

For more information, refer to the Running tests page.

Code quality

Sonar is used to analyse code quality. You can start a local Sonar server (accessible on http://localhost:9001) with:

docker compose -f src/main/docker/sonar.yml up -d

Note: we have turned off forced authentication redirect for UI in src/main/docker/sonar.yml for out of the box experience while trying out SonarQube, for real use cases turn it back on.

You can run a Sonar analysis with using the sonar-scanner or by using the maven plugin.

Then, run a Sonar analysis:

./mvnw -Pprod clean verify sonar:sonar -Dsonar.login=admin -Dsonar.password=admin

If you need to re-run the Sonar phase, please be sure to specify at least the initialize phase since Sonar properties are loaded from the sonar-project.properties file.

./mvnw initialize sonar:sonar -Dsonar.login=admin -Dsonar.password=admin

Additionally, Instead of passing sonar.password and sonar.login as CLI arguments, these parameters can be configured from sonar-project.properties as shown below:

sonar.login=admin
sonar.password=admin

For more information, refer to the Code quality page.

Using Docker to simplify development (optional)

You can use Docker to improve your JHipster development experience. A number of docker-compose configuration are available in the src/main/docker folder to launch required third party services.

For example, to start a postgresql database in a docker container, run:

docker compose -f src/main/docker/postgresql.yml up -d

To stop it and remove the container, run:

docker compose -f src/main/docker/postgresql.yml down

You can also fully dockerize your application and all the services that it depends on. To achieve this, first build a docker image of your app by running:

npm run java:docker

Or build a arm64 docker image when using an arm64 processor os like MacOS with M1 processor family running:

npm run java:docker:arm64

Then run:

docker compose -f src/main/docker/app.yml up -d

When running Docker Desktop on MacOS Big Sur or later, consider enabling experimental Use the new Virtualization framework for better processing performance (disk access performance is worse).

For more information refer to Using Docker and Docker-Compose, this page also contains information on the docker-compose sub-generator (jhipster docker-compose), which is able to generate docker configurations for one or several JHipster applications.

Continuous Integration (optional)

To configure CI for your project, run the ci-cd sub-generator (jhipster ci-cd), this will let you generate configuration files for a number of Continuous Integration systems. Consult the Setting up Continuous Integration page for more information.

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