1. The document discusses the development of a smart hydroponics system using artificial intelligence to optimize agriculture given increasing population and decreasing arable land. 2. It reviews literature on related smart agriculture systems using IoT and explores using hydroponics as an alternative to traditional agriculture. 3. The objectives are to design an AI-based hydroponic system architecture for different plants, build machine learning models to classify appropriate control actions, and validate the system through prediction testing.

1. Smart Hydroponics System using AI
Under the Guidance of:- Presented By:-
Dr. Mandeep Singh Ankit Chauhan
(Joint Director, CDAC Mohali) M-Tech, CDAC Mohali
Embedded System

2. Introduction
● Agriculture has a significant impact on the economy of the country. Humans require air, food, water, and living
space in order to survive. These things are not endless in nature and thus humans are dependent upon the
optimization of land area and the preservation of biodiversity.
● The human population is increasing and predicted to expand from 7.9 billion to 9.5 billion people within the next 40
years. An ever increasing demand for food species is implied, and it is estimated that food production will have to be
doubled in order to compensate and provide availability to all. However, with the increasing development, a lot of
agricultural land is being converted to non agricultural uses such as the construction of housing complexes,
industrial estates, trade zones and public facilities which will undoubtedly have a negative economic, social and
environmental impact.
● Agricultural methods using hydroponics are one of the possible alternatives to be able to do agriculture even
without extensive agricultural land.

3. Literature Survey
S.NO Author and Journal Method Features
1 LoRaWAN-based Smart Sewerage Monitoring
System
The author developed an IoT based
smart sewerage monitoring system
using a Node MCU, Sensors and LoRa
module
Used features are
LORAWAN, MQTT Protocol
for data sensing and
updating over the cloud
2 Experimental study on vented explosion
overpressure of methane/air
mixtures in manhole
The author developed a full-
scale manhole model in
which the explosion
overpressure of methane/air
mixtures
were studied experimentally.
Multiple ignition phases
were tested to verify the
percentage of methane
that will explode the
manhole cover.

4. Objective
1. Study and Design system architecture of AI-based Hydroponics system for different plants.
2. To build the best machine learning model and implementation of AI in Hardware towards the
classification of Control Action.
3. Validation of the system architecture and evaluating the predicting control action.

5. Structural Block Diagram

6. Sequence Flow Diagram

7. Implemented Objective
1. Completed the study of AI-based hydroponics system for different plants.
2. Completed the dataset for five plants(Spinach, Cabbage, Lettuce, Tomato, Basil).
3. Developed the Machine learning Model towards the appropriate control action for plants.
4. Developed the GUI for Different plants.

8. Input Parameters

9. Control Action with Labels

10. Datasets

15. ML Algorithms

20. Graphical User Interface