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Using IoT Sensors with AI for Smart Greenhouse Management

Cross-cutting
Digital Skills

IA Academy

Duration

3:00 p.m.

PRESENTATION

The "Predicting Pests in Crops Using AI" course offers you the opportunity to delve into a booming sector, where the demand for experts in advanced technologies for smart agriculture is growing. In a context where the food security It is crucial to have the ability to Predicting and Managing Pests with Artificial Intelligence has become essential. This course will provide you with the skills to integrate smart sensors, manage agronomic data y apply machine learning in greenhouses. You'll learn how to implement agricultural IoT systems, you will gain skills in data collection and analysis, and you'll find out how optimize automated decision-making for climate control, irrigation, and fertilization.

Objectives

  • Understanding the use of the IoT in Agriculture to improve efficiency.

  • Identify key sensors and actuators to optimize greenhouses.

  • Implement data collection and management techniques in the cloud.

  • Apply artificial intelligence for predict pest infestations effectively.

  • Design predictive models that optimize the climate and growing conditions.

  • Detect malfunctions in agricultural sensors using AI.

  • Automate decisions regarding irrigation and ventilation using smart systems.

Syllabus

TEACHING UNIT 1. THE IoT IN AGRICULTURE 1. The Internet of Things (IoT) 2. General architecture of an IoT system applied to agriculture 3. IoT communication protocols 4. Security and privacy in agricultural IoT systems TEACHING UNIT 2. SMART SENSORS AND ACTUATORS FOR GREENHOUSES 1. Classification and selection of sensors for key agronomic variables 2. Sensor integration: temperature, humidity, light intensity… 3. Actuators: control of irrigation, ventilation, lighting, and nutrients 4. Calibration, maintenance, and durability of sensors in harsh environments 5. Real-time data acquisition architecture and edge computing COURSE UNIT 3. AGRONOMIC DATA COLLECTION AND MANAGEMENT 1. Design of sensor networks and cloud storage 2. Data acquisition and transmission systems: gateways and nodes 3. Data visualization on IoT dashboards: key crop metrics 4. Data preprocessing: normalization, cleaning, and validation 5. Integration with agricultural management platforms TEACHING UNIT 4. APPLICATION OF ARTIFICIAL INTELLIGENCE IN GREENHOUSES 1. Fundamentals of AI and machine learning applied to the agricultural environment 2. Predictive models for indoor climate and growing conditions 3. Detection of anomalies and sensor failures using AI 4. Automated decision-making systems for irrigation, ventilation, and fertilization
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Are the Educa PHAROS courses eligible for credit?

Many courses can be credited toward the master's programs at Structuralia.
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Facts about our area

+ 1.483

Hours

+88.999

Minutes

264

Courses

Educa PHAROS is a next-generation training model that places a company’s human capital at the forefront. Through a platform that adapts to each company’s corporate identity and offers a total of more than 900 courses, it provides tailored training for each organization. The unlimited flat-rate plan provides each company with the number of courses that best suits its needs, as well as the ability to determine which employees will have access.
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