JFML: An open source Java Library for the IEEE Standard for Fuzzy Markup Language (IEEE Std 1855-2016)
JFML is an open source Java library which is aimed at facilitating interoperability and usability of fuzzy systems. Notice that JFML implements the new IEEE Std 1855 published and sponsored by the Standards Committee of the IEEE Computational Intelligence Society.
JFML has a web page associated with a complete documentation, a good variety of examples for both users and developers, etc., The web page is hosted at: http://jfml.es
From v1.3, JFML —now renamed as JFML-Core— is compiled with Java 11 and uses Maven to do so, whilst previous versions use Ant and Java 8. This module has two main purposes:
- It contains the definition of the main classes, such as FuzzyVariable.
- It applies an already built Fuzzy Logic System to a data set to predict the data output value.
To build, you can clone the .git repository or download the library into a .zip file from the Clone or download option. You can also download the source code from the releases in GitHub.
We recommend following the next steps to use it if no modification is needed:
- Download the library into a .zip file from the Clone or Download option or from the releases
- Unzip it in a local folder.
- At the root of the project, go (
cd) to Examples. - Run the following command:
java -jar ./lib/<jar-file> <problem> <fls> ./XMLFiles/<test-data-file>
This command is thoroughly explained in Examples/README-EXAMPLES.txt.
In case of changing the source files:
- Make the necessary changes.
- Do
mvn clean install. - A new artifact, as a JAR file, will be generated at the target folder.
- Copy and paste that JAR to Examples/lib.
- At the root of the project, go (
cd) to Examples. - Run the main command.
JFML IoT is an open source Java library designed to facilitate the integration of Fuzzy-Base Systems (FRBS) into Internet of Things (IoT) enviroments. Using Java Fuzzy Markup Language (JFML) as engine. It's available in github.com/JfMRes/JFML_IoT.
The entire project has been created with extensibility in mind. The abstract classes represent the basic functionality of all objects, making it easier to extend the project and add new classes to expand its capabilities.
You can download the full project or download the .jar file to import in your project from releases
This section provides an overview of the components implemented in the project.
The following sensors have been integrated into the system:
| Name | Variable | Type | Pin Count | Variable/Id Count |
|---|---|---|---|---|
| ArduinoNoiseSensor | Sound | Analog | 1 | 1 |
| ArduinoPotentiometer | Rotation | Analog | 1 | 1 |
| ArduinoFireSensor | Fire | Digital | 1 | 1 |
| ArduinoDHT11 | Temperature and Humidity | Analog | 1 | 2 |
| ArduinoSR04 | Distance | Analog | 2 | 1 |
| ArduinoLDR | Luminosity | Analog | 1 | 1 |
| ArduinoPIR | Presence | Digital | 1 | 1 |
| ArduinoPushButton | Interaction | Digital | 1 | 1 |
The following actuators have been implemented in the system:
| Name | Phenomenon | Type | Pin Count | Variable/Id Count |
|---|---|---|---|---|
| ArduinoLed | Light | Digital | 1 | 1 |
| ArduinoLedPWM | Light | Analog | 1 | 1 |
| ArduinoLedRGB | Light | Digital | 3 | 3 |
| ArduinoBuzzer | Sound | Digital | 1 | 1 |
| ArduinoServo | Mechanical | Analog | 1 | 1 |
The following embedded systems have been implemented in the system:
- Arduino Mega using OSOYOO MEGA-IoT Shield.
- NodeMCU v0.9
In the system, only the Message Queuing Telemetry Transport (MQTT) protocol has been implemented for communication, as it provides highly efficient and secure communication.