Author: Dariu-Admin

In many schools, technology is still used mainly for basic learning support. Inspired by the Industry 4.0 revolution, a team of students set out to change that — by building a physical robot integrated with an AI-based chatbot. The robot can assist teachers and students in quickly accessing lesson-related information, make learning more interactive and enjoyable, and act as a friendly classroom companion capable of recognising emotions and responding to users’ moods.

HOW DOES IT WORK?

The robot combines AI, IoT and voice recognition to enable natural, two-way communication. Built on the Yolo:Bit programmable board with Wi-Fi and Bluetooth connectivity, it uses a chatbot engine with natural language processing to generate conversational responses across multiple subjects — from Math and Science to English. The hardware includes a mini-computer, touchscreen interface, 4G SIM module, power board and sensors. The system can also monitor classroom conditions such as temperature and lighting, and can be controlled via smartphone. Students program multi-topic responses themselves, making the robot a versatile educational assistant that can help with homework, answer questions and interact in a friendly, engaging way.

Flooding and saltwater intrusion are growing challenges in the Mekong Delta, particularly in Hau Giang Province. Seasonal flooding combined with irregular high tides and rising sea levels causes water levels to fluctuate unpredictably, leading to residential flooding and damage to daily living environments. During the dry season, saltwater intrusion threatens freshwater storage in tanks, ponds and household systems. Manual monitoring is time-consuming, inaccurate and ineffective under rapidly changing conditions. A team of students developed this automated system to help communities protect freshwater sources, reduce flood risks and respond promptly to environmental changes.

HOW DOES IT WORK?

Water level sensors continuously measure the height of water in tanks, ponds or drainage areas and send data to a central microcontroller. The controller compares incoming data with pre-set safe thresholds and, when water rises above or drops below these limits, automatically activates pumps or drainage valves to regulate the water level. By maintaining water within a safe range, the system helps prevent flooding during high tides and reduces the risk of saltwater entering freshwater storage. An integrated IoT module (ESP32) uploads data to a web or mobile application, allowing users to monitor water levels remotely and receive timely alerts. This automated approach ensures continuous protection, faster response times and improved water management for households and flood-prone communities.

The AI Smart Chair for the Elderly and Disabled was developed by Huynh Minh Trong and Nguyen Hoang Huy, students from Tra On High School, Vinh Long Province, under the guidance of Mr. Tran Trong Huu, Physics Teacher. The project won First Prize in the Vinh Long Provincial Science and Technology Competition 2025–2026 for its innovative use of artificial intelligence (AI) and Internet of Things (IoT) technologies to enhance mobility, health monitoring, and safety for vulnerable individuals.
Vietnam’s aging population faces daily challenges related to limited mobility and a high risk of falls, while most smart chair solutions remain expensive and ill-suited to the Vietnamese physique. This project set out to design an affordable, intelligent chair tailored to local needs—helping users live more independently, comfortably, and safely.

HOW DOES IT WORK

The AI Smart Chair combines smart sensors, motorized functions, and AI-assisted control systems to support users in multiple ways:
• Adaptive posture adjustment: The automated backrest allows users to lift or recline the seat for comfort, reducing fatigue and the risk of bedsores.
• Real-time health monitoring: Sensors measure heart rate, blood oxygen (SpO₂), and temperature, transmitting the data via an ESP32 microcontroller to the Firebase Realtime Database. If readings exceed safe limits, the mobile app built with React Native sends instant alerts to caregivers.
• Multiple control options:
• Button control: Quick commands for core actions such as name announcements and power switches.
• Voice control: Integrated with Google Gemini AI and Google Home through IFTTT, allowing hands-free operation.
• Eye and head control: Using CameraX and Google ML Kit, the chair recognizes blinks and head rotations as commands—for example, two blinks to trigger an emergency alert or three blinks to request hygiene support.

IMPACT

The AI Smart Chair demonstrates how young innovators can use technology to promote inclusion and care. By merging AI, IoT, and practical design, the project provides elderly and disabled individuals with greater autonomy while easing the workload of caregivers—a powerful example of how innovation can directly improve lives in Vietnam’s communities.

The Semi-Automatic Durian Harvesting and Transport project was developed to address safety and efficiency challenges in durian farming. In provinces such as Vinh Long, Tien Giang, and Ben Tre, durian harvesting still relies heavily on manual labour, exposing workers to safety risks from climbing tall trees and handling heavy, thorny fruits. Traditional machines are unsuitable for durians due to their unique weight, protective needs, and delicate handling requirements. The team set out to create a Bluetooth-controlled automated system that reduces physical strain, enhances worker safety, and protects fruit quality throughout the harvesting and transport process.

HOW DOES IT WORK

The system operates through a smartphone interface connected via a Bluetooth Module (BT18), with an UNO R3 microcontroller at its core processing commands and controlling DC motors through BTS7960 motor drivers across three channels:

• Remote positioning: The operator uses a smartphone app to navigate the machine beneath durian trees, eliminating the need for climbing
• Safe harvesting platform: Workers cut durians from a stable platform while fruits drop gently into a cushioned catchment basket, preventing damage
• Controlled lowering: The basket descends slowly into the main container, protecting fruit quality and integrity
• Automatic transport and unloading: Once full, the machine navigates to the collection point and tilts the basket to transfer fruits onto trucks effortlessly

The system functions seamlessly from orchard to collection point. In the field, operators position the machine under high durian trees, cut the fruit, and watch it land safely in the basket. During collection, the machine automatically moves to the pickup area and tilts to load fruits onto transport vehicles, saving time and reducing manual handling.

IMPACT

The Semi-Automatic Durian Harvesting system combines automation, IoT, and agricultural technology to create a practical solution for real-world needs. It demonstrates how students can apply coding, engineering, and problem-solving skills to address meaningful community challenges—from improving worker safety to modernising traditional farming practices in Vietnam’s Mekong Delta region.

The AutoSense Bed project was developed with the vision of using technology to improve healthcare and caregiving. In many Vietnamese families, especially those with elderly or sick members living alone, providing constant care can be challenging. The team set out to create an automated system that monitors health conditions, reduces caregiver workload, and ensures patients receive timely attention—particularly when professional healthcare support is limited.

HOW DOES IT WORK

The AutoSense Bed integrates health monitoring, mobility assistance, and remote control into one comprehensive system. At its core, an ESP32 ESP-WROOM-32 microcontroller collects and processes health data from multiple sensors:

• A GY-MAX30100 sensor continuously measures heart rate and blood oxygen levels
• An arm-style blood pressure monitor records blood pressure and pulse
• A GY-906 MLX90614 infrared temperature sensor measures body temperature without contact, ensuring patient comfort and hygiene

All readings are displayed on a local screen and transmitted via Wi-Fi or Bluetooth to a mobile application, allowing caregivers to monitor the patient’s condition remotely from anywhere.

Additionally, the bed’s mechanical system—powered by a stepper motor and T20 lead screw—enables smooth lifting, lowering, and repositioning of the patient. Caregivers can adjust these settings through the mobile app, ensuring safety and convenience even when they’re not physically present.

IMPACT

The AutoSense Bed combines automation, IoT, and healthcare technology to create a practical solution for real-world needs. It demonstrates how students can apply coding, engineering, and problem-solving skills to address meaningful community challenges—from supporting elderly care to improving home healthcare systems in Vietnam.

In response to declining air quality caused by environmental pollution and climate change—particularly the dry conditions created by air conditioner use—a talented student from Long Tri A Secondary School has developed an innovative automatic mist humidifier. This groundbreaking project maintains optimal humidity levels, reduces temperature, protects health, and conserves energy while addressing the limitations of traditional humidification methods in agriculture, especially within greenhouse environments.

HOW DOES IT WORK

The automatic mist humidifier system combines advanced components to efficiently monitor and regulate environmental conditions through four key processes:

Data Collection
DHT11/DHT22 sensors continuously measure temperature and humidity, transmitting real-time data to the control unit for immediate analysis.

Signal Processing
The central control circuit (Arduino/ESP32) analyzes sensor data and compares it against pre-configured thresholds to determine necessary adjustments.

Automated Adjustment
When humidity drops below the set threshold, the system activates the ultrasonic mist humidifier to increase moisture levels. If temperature exceeds the allowed limit, the TEC-12706 Peltier cooler activates to cool the air. Once desired levels are achieved, the system automatically shuts off to conserve energy and water.

Continuous Operation
This process repeats continuously, ensuring a stable and optimal environment at all times.
The system shows excellent potential for future enhancements, including integration with mobile applications for remote monitoring and adjustment, as well as incorporating self-learning algorithms to optimize operating parameters over time.

Large-scale laundry facilities currently rely on a manual fabric color sorting process that is time-consuming and costly. This method also exposes workers to potential health hazards from contaminants on clothing. In addition, there is a need for an automated solution to help individuals with visual impairments or other disabilities quickly classify fabric colors. This project proposes and develops an automated “Fabric Color Sorting System” to address these issues by accurately identifying and separating white fabrics from colored fabrics.

HOW DOES IT WORK

The system provides precise identification and separation of white and colored fabrics. This innovative solution integrates several advanced components mounted on a lightweight aluminum frame.

• Keyence color sensors
• Photoelectric sensors
• Robotic cylinders
• Vacuum suction systems
• Mitsubishi PLC control
• Intuitive HMI touch interface

The system can process six samples (two white, four colored) in 55 seconds, automatically sorting them into designated bins. This automation reduces labor costs, increases operational efficiency, and improves worker safety by minimizing contact with contaminated materials. The system also creates a more inclusive environment by increasing accessibility for people with visual impairments.

This solution modernizes laundry operations and creates safer, more inclusive working environments