The UCRIX 2024 Exhibition

The VoteWise project is a mobile application designed to modernize and simplify the voting process for organizations. By leveraging digital technology, the app enables secure, transparent, and convenient voting, allowing users to participate from anywhere. Key features include easy registration, real-time results viewing, and enhanced accessibility for all users. Additionally, VoteWise aims to reduce the environmental impact by minimizing paper use in the voting process. The app addresses contemporary needs for efficiency, inclusivity, and trust in the voting system.

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TEAM MEMBERS:

Nur Allieysa Mohd Ghani

Nik Qistina Nurin Nik Shaiful Anwar

Nurul Jannah Hasnaa Hisham

Fatima Az-Zahrah binti Mohamad Fadzli

PONMUGILLAN A/L MANI

This project, referred to as GLU@U, is an intelligent management system for people with abnormal glucose metabolism, integrating the three modules of real-time continuous monitoring system for blood glucose, blood oxygen, blood pressure, electrocardiogram, and body temperature (intelligent hardware), data management intelligent analysis+decision-making system (SaaS, Software as a Service), and healthcare care management. It mainly utilizes rtCGM, AI, cloud computing, IoT and other technologies to integrate the user's blood glucose, ECG, temperature and other data collection and analysis, the hospital-side SaaS system and the personal version of the health management APP, to form a closed loop of digital health monitoring+management inside and outside the hospital. The healthcare operation and service system built by AiSugar, as well as the Internet cloud computing platform support system, constitute the intelligent monitoring of AiSugar's “artificial intelligence + chronic disease” and the multi-dimensional operation of the whole scenario of digital healthcare and health management.
The system combines offline and online blood glucose management to achieve integrated blood glucose management in and out of hospitals, including home-based management of diabetes, which is an advanced and effective model for fine management of diabetes. At the same time, the system expands the real-time monitoring, data analysis, intelligent assessment and remote medical care management of multiple vital signs or important parameters, which is an innovative application for the fine management of multiple chronic diseases.

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TEAM MEMBERS:

JiaoFenglei

JiangAnqi

Zhanghua

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Smart Waste AI is a cutting-edge waste management solution system designed to optimize and streamline the process of waste sorting and distribution using advanced deep learning technology.

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TEAM MEMBERS:

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MUHAMMAD LUQMAN ARIF MOHAMAD

NURUL ANIS SYAHIRAH ADENAN

NUR ALYA SYAHIDAH ADENAN

This project targeted at discover the hybrid Recurrent Neural Network (RNN) algorithm that can outperform standalone algorithms which are Long Short Term Memory (LSTM), Auto Regressive Integrated Moving Average (ARIMA), Convolutional Neural Network (CNN) and Convolutional LSTM (ConvLSTM). In this project, we have used ARIMA-LSTM as our hybrid Recurrent Neural Network (RNN) algorithm.

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TEAM MEMBERS:

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DIRNESIVAM A/L K GAJAINTHIRAN

Deloria Shaniska Razin

​Sharifah Shalwa Syed Sulaiman

Most of the patient that undergo surgery will need to take care of the incision as it
heals. By doing so the patient will be able to limit scarring, may help avoid any pain or
discomfort and most importantly help minimize the possibility of infection. By taking
care it means, keep the area clean or change the dressing according to doctor’s
instructions and watch out for signs of infections. From the view of a patient, at a glance
the incision area might appear to be fine, but from the perspective of a professional, it
might mean the other way. The only way is to let professional to look at the incision area
but making a trip to the hospital to do checking maybe inconvenient to some. So, it would
save a lot of time if there is an application that will allow patient to submit their
wound/incision area to a doctor to monitor.

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TEAM MEMBERS:

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ROHANA MYDIN

SITI SARIPA RABIAH MAT LAZIM

​NURRUL IZZA MAD NOH

The project aims to develop A Conceptual Edge Computing Framework Leveraging Embedded Agent in a 5C Cyber-Physical System Architecture for Sustainable Space Agriculture to help optimize plant growth in space environments like the International Space Station. Growing food in these habitats poses challenges like power, bandwidth and crew time in space, as well as the need for real-time constant environmental monitoring and decision making. Our solution integrates small edge devices running machine learning with sensors inside the plant chamber. This will allow automated management of the chamber's systems to maximize plant health with minimal human input. This embedded device implementation is proposed within a 5C Cyber-Physical System Architecture to seamlessly enhance the process. Researchers overseeing long-term experiments on stations will benefit from this intelligent system supporting their work. Overall, our goal is to help sustainability of food production in space also enhances data-driven research and automated decision making. We think technologies like edge and fog computing are well-suited for the task. If successful, it could advance how we grow food for long-term space missions!

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TEAM MEMBERS:

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Vishwareena Vanoo

Mohammad Yusnisyahmi Yusof

Asif Karim

Our team is working on a Goat Face Recognition Using Deep Learning for Enhanced Animal Identification, in this case for goat face detection. A face recognition system allows for automatic livestock identification, including goats, cows, and other livestock. This idea can be further developed to identify health issues that are detectable by changes in the facial structures of livestock. It can also be taken in the direction of maturity detection, detecting different facial features signifying the life stages of the livestock.

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TEAM MEMBERS:

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MUHAMMAD IKHWAN HAZIQ KHAIRUL ANUAR

CHAN YI HERN

NIK NUR ALIA MOHD SAUFI

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Rice Rescue is a professional, Smart Farming App, with Precision Data & AI Driven Technology for paddy care from seed to harvest 🌱

Features 📱
1. Hyperlocalisation Mapping 🔎
Utilize our precise mapping feature to delineate and mark your farming locations. Draw maps directly within the application, allowing you to visualize and strategize your farming activities with precision.

2. AI Plant Health Analysis 🤖
Provides insights on nutrient levels for disease detection with a simple snap-and-go

4. Pest and Disease Detection 🐀
Scout your paddy fields for signs of pests and diseases, and practices for effective control. Our application utilizes IoT technology and machine learning algorithms to identify pests and their locations, empowering you to make informed decisions and safeguard your crops.

5. Task Creation 📝
Streamline the farming process by creating tasks tailored to your paddy cultivation needs. Our intuitive interface guides you through task creation, ensuring efficiency and accuracy in managing your farm operations.

6. Team Management 👥
Optimized tasks and seamless team management for efficient paddy operations. This is useful for if you have big team members.

7. Weather Monitoring 🌤️
Stay informed about the weather conditions that impact your paddy cultivation. Our app integrates with weather data sources to provide real-time updates on temperature, rainfall, humidity, and other relevant meteorological factors, helping you plan your farming activities accordingly.

8. Tailored Education 📚
Access a comprehensive database of educational resources and best practices tailored to paddy farming. Our app offers interactive tutorials, video guides, and expert-curated content to help you continuously improve your farming techniques and stay up-to-date with the latest advancements in the industry.

9. IoT Moisture and Temperature Integration 🌱 - PaddyX
Leverage the power of IoT technology to monitor the soil moisture and environmental conditions in your paddy fields. Our app seamlessly integrates with wireless sensors and smart devices, providing real-time data insights to optimize irrigation, nutrient management, and overall crop health.

10. Machinery Management 🚜
Efficiently manage your farm machinery and equipment. Our app allows you to track the usage, maintenance, active and inactive of your tractors, harvesters, and other agricultural tools, ensuring optimal operational efficiency and minimizing downtime.

11. Farmer's Marketplace 🛒
Access a thriving online marketplace where you can see al paddy-related products, services, and equipment. Connect with a community of fellow farmers, suppliers, and industry experts to expand your business opportunities and access a wider range of resources.

12. Chatbot & Live Forum 🤖
Paddy farming support through our chatbot and live community forum

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TEAM MEMBERS:

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HAZIQ HAKIMI BIN MAZLISHAM

MUHAMMAD HAKIM BIN ZULKHAINAN

HARIS AZHARI BIN ZAHARUDIN

MUHAMMAD IRFAN BIN ABDUL GHAFAR

FreshRescue, a groundbreaking initiative tackling the critical issue of food waste through innovative technology and strategic collaboration.

Powered by Flutter, Firebase, TensorFlow, and Gemini AI, FreshRescue is not just a solution but a revolution in sustainable food management. Our holistic ecosystem effectively closes the loop on food waste through prevention, utilization, and disposal, fostering responsible consumption and a sustainable community.

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TEAM MEMBERS:

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Chai Kok Cheng

Chan Ci En

Yong Jun Wei

MyKebun is an easy to use crop care & protection designed to help small scale and new farmers in caring their crops. MyKebun developed using Flutter with AI modeled using Teachable Machine and TensorFlow, it also gathers real time weather data through open API from Open-Meteo. The app features pest & disease identifaction AI, environment monitoring system and able to generate solutions & recommendations. MyKebun is your green thumb solutions... now at your fingertips!

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TEAM MEMBERS:

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Lukman Hakim Ilias

Muhammad Norman Samsudin

Muhammad Aiman Irfan Shahrel

Surplus2Serve is a project aimed at tackling hunger and reducing food waste. It connects restaurants with surplus food to authorized volunteers who redistribute it to those in need. By addressing this issue, the project supports several Sustainable Development Goals, including No Poverty, Zero Hunger, Responsible Consumption and Production, and Sustainable Cities and Communities. Potential users include restaurants with excess food, volunteers who manage the redistribution, and recipients who benefit from the donated food. Surplus2Serve turns what would be waste into valuable resources for communities, ensuring that excess food serves a purpose rather than ending up in landfills.

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TEAM MEMBERS:

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MUHAMMAD ALIF SYAHMI NORMAHADI

MUHAMAD BADAR MIQDAD MD NASIR

​AQIL DANISH MOHAMMAD YUSOF