Food Waste Reduction Using IoT and Smart Sensors
Smart Solutions for Sustainable Food Systems
Skills you will gain:
Food waste is a global challenge that demands innovative and technology-driven solutions. This program focuses on the application of IoT and smart sensors to monitor, analyze, and optimize food production, storage, and transportation processes. Participants will learn how to implement real-time tracking systems, predictive analytics, and automated solutions to minimize food loss and waste.
The program combines theoretical insights with hands-on experience, enabling participants to design and deploy IoT-based solutions tailored to food waste management. It covers the integration of smart sensors with IoT platforms, data collection, and interpretation for informed decision-making, ultimately promoting a sustainable and efficient food supply chain.
Aim: To leverage IoT and smart sensor technologies in reducing food waste across supply chains, enhancing sustainability, and improving operational efficiency in agriculture, storage, and distribution.
Program Objectives:
- Understand the role of IoT and smart sensors in food waste management.
- Learn to design systems for real-time monitoring of food storage and transportation.
- Explore predictive analytics for food spoilage prevention.
- Gain expertise in integrating smart technologies with sustainable practices.
- Develop strategies to reduce waste and improve food security.
What you will learn?
Week 1: Foundations of Food Waste & Smart Systems
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Overview of global food waste challenges and statistics
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Deep science behind food spoilage processes
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Introduction to IoT and deep tech in food logistics
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Sensor fundamentals: temperature, humidity, gas, and motion detection
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Workflow from real-time sensing to actionable insights
Week 2: IoT Network Architecture & Smart Deployment
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IoT hardware components and microcontroller integration
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Communication protocols: MQTT, LoRa, NB-IoT
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Power management and sustainability in sensor networks
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Data collection frameworks and cloud interfacing
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Designing smart bins and storage monitoring systems
Week 3: Data Processing, Analytics & Visualization
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Real-time data logging, preprocessing, and transmission
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Smart analytics: pattern recognition for spoilage prediction
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Dashboard creation and visualization tools (e.g., ThingsBoard, Node-RED)
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Data-driven alerts and decision-making automation
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Case studies on food shelf-life extension via IoT
Week 4: Deep Tech Innovation & Field Applications
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Advanced sensor fusion for high-accuracy detection
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Machine learning models for waste classification
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AI-enabled supply chain optimization
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Pilot deployment strategies and field trials
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Ethical, policy, and translational considerations in smart food tech
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Intended For :
- Undergraduate degree in Environmental Science, Food Technology, Computer Science, or related fields.
- Professionals in the food and agricultural industries.
- Individuals with a keen interest in IoT, sustainability, and smart technologies.
Career Supporting Skills