Level 1: System Context

At the highest level, the System Context Diagram depicts the system as a single box surrounded by its external entities, such as users, systems, and external dependencies. This diagram provides a broad view of the system and its interactions with the outside world. It helps stakeholders understand how the system fits into its larger environment, the external actors it interacts with, and the boundaries of the system.

The next figure shows the architecture at level 1:

L1: Users

The platform serves as a comprehensive solution to support decision making process, catering to the needs of researchers, decision-makers, farmers, and extension agents. Researchers are people who analyze and configure data into the system, while decision-makers rely on its insights to make informed choices. Farmers benefit from information and recommendations for agricultural practices, and extension agents facilitate effective communication and support.

L1: AClimate system

AClimate system serves as a vital component, providing valuable insights and predictions. This system acts as a central hub that generates forecasts directly into the platform. It establishes connections to obtain relevant data from diverse sources, ensuring the availability of accurate and up-to-date information. Leveraging additional applications and tools, the system employs advanced algorithms and models to generate forecasts specific to agroclimatic conditions. Furthermore, it incorporates crop simulation techniques to simulate the growth and development of crops under different climatic scenarios. By integrating these capabilities.

L1: Melisa

Melisa Chatbot is an innovative chatbot system designed to provide agroclimatic information using Natural Language Processing (NLP) techniques across various social media and messaging platforms. As a cutting-edge AI-powered chatbot, Melisa utilizes advanced language understanding algorithms to interpret user queries related to agroclimatic conditions and provide timely and accurate responses. By leveraging NLP capabilities, Melisa can analyze and understand the intent and context of user messages, ensuring personalized and contextually relevant information is delivered. This chatbot system acts as a virtual assistant for farmers, researchers, and other stakeholders, offering on-demand access to agroclimatic data, forecasts, and recommendations. Melisa is not part of this documentation, you can find more information in Melisa news