
NO. |
PROJECT TITLE |
TYPE |
DESCRIPTION |
TRL |
ESTIMATED COST |
STATUS |
DETAILS |
|
|---|---|---|---|---|---|---|---|---|
1 |
|
VEDIWARD
UNIVERSITI TEKNIKAL MALAYSIA MELAKA |
Research |
VEDIWARD IS A DYNAMIC ROLL INSTABILITY WARNING DEVICE FOR COMMERCIAL VEHICLES. IT IS DESIGNED TO SOLVE THE COMMERCIAL VEHICLE ACCIDENTS CAUSED BY THE ROLL INSTABILITY. AN EARLY WARNING INDICATOR OF AN IMPENDING VEHICLE ROLLOVER IS ESSENTIAL, ESPECIALLY TO THE COMMERCIAL VEHICLE DRIVER IN ORDER TO CONTROL THE VEHICLE AND EVENTUALLY AVOIDS THE ROAD ACCIDENT. IN ORDER TO OVERCOME THIS PROBLEM, THE DYNAMIC ROLL INSTABILITY WARNING DEVICE FOR COMMERCIAL VEHICLES INTEGRATED WITH THE ROLLOVER INDEX ALGORITHM, DRIVER STEERING AND VEHICLE SPEED INPUTS IS PROPOSED. THE DYNAMIC ROLL INSTABILITY WARNING DEVICE PERFORMANCE IS EVALUATED BY CONDUCTING THE EXPERIMENT INVOLVING THE STEP-STEERING MANEUVERS, SUBJECTED TO VARIOUS SPEEDS AND LOAD CONDITIONS IN THE TRUCKSIM DRIVING SIMULATOR AND MATLAB/SIMULINK SOFTWARE. IT IS OBSERVED FROM THE EXPERIMENT RESULTS THAT THE DYNAMIC ROLL INSTABILITY WARNING DEVICE PRODUCED 12.4% FASTER TIME-TO-WARN THAN THE DYNAMIC ROLL INSTABILITY WARNING DEVICE AVAILABLE IN THE MARKET FOR THE DRIVER AND OFFERS ADEQUATE TIME-TO-RESPOND TO INITIATE THE CORRECTIVE ACTIONS. THUS, THE DYNAMIC ROLL INSTABILITY WARNING DEVICE PROPOSED A BETTER EARLY WARNING SYSTEM AND PREVENT ROLLOVER ACCIDENT SIGNIFICANTLY. |
-
|
RM1,000.00
|
PROPOSAL
|
|
2 |
|
IMPLEMENTATION OF GENERATIVE AI IN DEVELOPMENT OF A PLAYER-CENTRIC ADAPTIVE SYSTEM OF A HOLOGRAPHIC GAME
UNIVERSITI TEKNIKAL MALAYSIA MELAKA |
Research |
POWERED BY GENERATIVE AI, THIS ADAPTIVE HOLOGRAPHIC SYSTEM TRANSFORMS IMMERSIVE GAMEPLAY INTO AN INTELLIGENT PROFILING TOOL. USING REAL-TIME PLAYER BEHAVIOR ANALYSIS AND BARTLE PROFILING, THE SYSTEM DYNAMICALLY ALTERS SCENARIOS BASED ON LIVE USER ACTIONS. IT EMPOWERS RECRUITING, TRAINING, AND EVENT MANAGEMENT COMPANIES TO OBJECTIVELY EVALUATE CANDIDATES, TRAINEES, AND ATTENDEES. OBSERVING AUTHENTIC DECISION-MAKING WITHIN INTERACTIVE HOLOGRAPHIC ENVIRONMENTS GIVES ORGANIZATIONS VALUABLE BEHAVIORAL INSIGHTS FOR DATA-DRIVEN TALENT PLACEMENT, SKILL ASSESSMENT, AND AUDIENCE ENGAGEMENT ANALYSIS. |
-
|
RM60,000.00
|
PROPOSAL
|
|
3 |
|
NODEREVEAL
UNIVERSITI MALAYSIA SABAH |
IP |
NODEREVEALâ„¢ IS A BREAKTHROUGH PATHOLOGY INNOVATION TO ADDRESS A CRITICAL DIAGNOSTIC FLAW WHICH MISSED CANCER METASTASES FROM UNDETECTED LYMPH NODES. OUR PROPRIETARY, READY-TO-USE TISSUE-CLEARING SOLUTION DRAMATICALLY INCREASES LYMPH NODE HARVEST YIELD WHILE FULLY PRESERVING CELLULAR INTEGRITY FOR DOWNSTREAM HISTOPATHOLOGY AND IHC TESTING. IN CLINICAL OUR CLINICAL STUDIES, NODEREVEALâ„¢ HARVESTED 482 ADDITIONAL UNDETECTED LYMPH NODES, REVEALED 21 UNDETECTED CANCER METASTASES, AND UPSTAGED 7 PATIENTS TO ACCURATE, LIFE-SAVING CANCER TREATMENT. CURRENTLY, OPERATING AT TRL 7, WE SEEK STRATEGIC INVESTMENT AND PARTNERS TO ACHIEVE ISO 13485/MDA REGULATORY APPROVAL AND SCALE COMMERCIAL DISTRIBUTION ACROSS ASEAN.
TO UNDERSTAND IT BETTER PLEASE WATCH THIS VIDEO: HTTPS://YOUTU.BE/I2MDZWB6RDM?SI=UUP_-4PXBUCDUACW |
-
|
RM10,000,000.00
|
COMPLETED
|
|
4 |
|
AI-BASED SYSTEM FOR VERIFICATION OF VEHICLE EXAMINERS AND CORRESPONDING INSPECTED VEHICLES USING DEEP LEARNING TECHNIQUE
UNIVERSITI TUN HUSSEIN ONN MALAYSIA |
IP |
"THIS PROJECT PROPOSES AN AI-POWERED VISUAL INTELLIGENCE PLATFORM TO IMPROVE THE ACCURACY, EFFICIENCY, SAFETY, AND SECURITY OF INSPECTION PROCESSES ACROSS VARIOUS INDUSTRIES. CONVENTIONAL INSPECTIONS OFTEN DEPEND ON MANUAL DATA ENTRY, VISUAL OBSERVATION, AND PERSONNEL VERIFICATION, WHICH MAY LEAD TO HUMAN ERROR, INCONSISTENT RECORDS, UNAUTHORISED ACCESS, AND DIFFICULTY TRACKING INSPECTION ACTIVITIES.
THE PROPOSED PLATFORM APPLIES DEEP LEARNING AND COMPUTER VISION TO RECOGNISE AUTHORISED PERSONNEL, IDENTIFY AND TRACK RELEVANT OBJECTS, MONITOR PERSONNEL MOVEMENT, VERIFY SAFETY-WEAR COMPLIANCE, AND PROVIDE REAL-TIME ALERTS. BY AUTOMATING THESE ACTIVITIES, THE PLATFORM STRENGTHENS INSPECTION INTEGRITY, REDUCES MANUAL ERRORS, STANDARDISES PROCESSES ACROSS MULTIPLE LOCATIONS, AND IMPROVES OVERALL OPERATIONAL EFFICIENCY." |
-
|
RM500,000.00
|
PROPOSAL
|
|
5 |
|
DRIVEPULSE: AN AI-POWERED SYSTEM FOR REALTIME DRIVING BEHAVIOR ANALYSIS
UNIVERSITI TEKNIKAL MALAYSIA MELAKA |
Research |
DRIVEPULSE IS AN INNOVATIVE, SMARTPHONE-BASED TELEMATICS PLATFORM THAT LEVERAGES ON-DEVICE ARTIFICIAL INTELLIGENCE TO REVOLUTIONIZE ROAD SAFETY WITHOUT REQUIRING EXPENSIVE EXTERNAL HARDWARE. BY ANALYZING BUILT-IN SENSOR STREAMS IN REAL TIME, THE APPLICATION CLASSIFIES DRIVING BEHAVIORS, PROVIDES LIVE COLOR-CODED MAP COACHING, AND TRIGGERS AUTOMATED EMERGENCY SOS ALERTS DURING CRITICAL IMPACT EVENTS. DRIVEPULSE DIRECTLY EMPOWERS DRIVERS TO ELIMINATE AGGRESSIVE HABITS, PROMISING TO DRASTICALLY REDUCE HUMAN-ERROR ACCIDENTS, IMPROVE FUEL EFFICIENCY, MINIMIZE VEHICLE MAINTENANCE COSTS, AND DELIVER A SCALABLE, DATA-DRIVEN SOLUTION FOR THE FLEET AND USAGE-BASED INSURANCE INDUSTRIES. |
-
|
RM150,000.00
|
PROPOSAL
|