CREST Design Challenge

Design Challenge 1: Smart Transportation

In order to achieve the smart city status, the residents, infrastructure, and connectivity (either IoT or Internet) are the key components for the movement. First thing is to get the infrastructure to be connected and make sure the connectivity is available for any smart city projects. Also, the engagement and involvement of the people are essential as they are the users and will be benefited by the smart city applications.

One of the biggest challenges faced by the cities today is to keep improving mobility and decreasing traffic congestion, provide transportation for many people and goods. Congestion is one of the biggest problems that directly impact the daily activity of commuters, businesses, and visitors to the city. To overcome this problem, solution for smart transportation is needed to reduce the transportation core problem as well as to optimize the use of city public transport.

  • Utilizing the infrastructure as a platform (streetlight, traffic light, bus stop, street poles, bridges, etc.)
  • AI technology and IoT connectivity (LoRa, 6LowPAN, Zigbee, 4G-WiFi, 5G, etc.)
  • To improve the connectivity of infrastructure, mobility of people and transportation (bus, car, train, etc.)

CREST Innovative and Intelligent City cluster welcomes solutions that solved one or more of the infrastructures’ connectivity, mobility, and transportation issues. The solution needs to demonstrate working prototype/demo as proof of concept to showcase the whole solution.

Design Challenge 2: Predictive Manufacturing Quality

In manufacturing of finished products, the assembly line is the main of total manufacturing process in which parts are combined and assembled as the semi-finished parts moves from workstation to workstation (or process to process) where the parts are added in sequence until the final assembly or product is produced. The quality of the finished assembly is usually assessed at the end of the assembly line, which by then, resources such as materials, machine utilization and people would have already been invested.

Similar process steps are found in various manufacturing facilities either electronics, plastic, metal parts or a combination of these components or sub-systems. Finding out quality issues towards the end of the assembly line will be very costly due to the investments made earlier. Relating the end product quality to machine settings and performance and components or sub-system level in-process quality monitoring will be essential. Adoption or computer vision or machine vision plus other sensors detecting noise, vibration, optical/light signals, RF parameters would be critical for predicting and preventing quality issues in final product, thus higher productivity and value to manufacturers.

Predict the end quality of finished goods in the early production stages and/or performance of manufacturing equipment or processes before equipment breakdown and processes halted resulting in loss of productivity and low product quality.

Develop a predictive model trained based on historical datasets (images, sound, vibration, etc.) on quality of finished goods and components level, and front end processes. The model will then be used to predict the quality of finished products early in the production stages.

Design Challenge 3: Precision Farming

Intelligent solutions that improve cost, time and quality of production of agriculture produces based on Industry 4.0 technologies

Malaysia agriculture sectors are still largely operated very manually and prime for opportunities for digital transformation. Advent of Industry 4.0 technologies such as automation and mechanization, autonomous vehicles, data science and analytics, machine learning, artificial intelligence, drones, block chain, cyber physical system, cloud computing, augmented reality, etc. provides avenues for digital innovation and transformation of agriculture supply chain from seeds, growing, cultivation, harvest, post processing to market.

The challenge is to empathize, conceptualize, develop, design and demonstrate solution through any I4.0 or digital technology to improve COST, TIME or QUALITY of agriculture, aquaculture or livestock process and supply chain.

Develop a solution that is intelligently detecting and controlling the variables that govern the growth of agriculture system such as banana, fig, paddy, oil palm, pineapples, or simply vegetables that lead to optimum growth conditions that improve cost, time and quality of the produce. An algorithm is developed based on learned parameters and growth behaviour for the optimum performance.

Design Challenge 4: Digital Healthcare

Medication adherence usually refers to whether patients take their medications as prescribed as well as whether they continue to take a prescribed medication. Medication non-adherence is a growing concern to clinicians, healthcare providers and other stakeholders because of mounting evidence that it is prevalent and associated with adverse outcomes and higher costs of care. To date, measurement of patient medication adherence and use of interventions to improve adherence are rare in routine clinical practice. This non-adherence is more prevalent in some specific groups of people, for example in senior citizens, diabetic patients and people who reside in rural areas. Depending on the complexity of the prescribed medication regimens, generally 40% - 50% of patients do not adhere to their medications.

Design a solution to alleviate this medication non-adherence issue. The idea can cover the development of any monitoring system in the forms of wearables, smart pills, etc. The solution should emphasize on low-cost, non-invasive, effective and reliable approach.

Impacts & Benefits of Taking Up the Challenge

The Great Lab (TGL) Project Funding

Teams shortlisted under the CREST track will be eligible to apply for a project seed fund of RM1,500 per team under The Great Lab (TGL) Project Funding program. The TGL project seed fund is intended to cover the project materials cost of each team during product development stage. Teams will be required to submit application documents via CREST online platform and attend an interview with CREST panel. Further terms and conditions is published in CREST online platform.

Fund application

CREST is the brainchild of a group of passionate people representing the interest of 3 key stakeholders of Malaysia’s E&E Industry — the Industry itself, the Academia, and the Government.

Launched in 2012, CREST was formed to address Malaysia’s E&E needs for:

  • An industry-led organisation to drive R&D innovation
  • A platform for local & MNC companies to form a formidable R&D ecosystem
  • A sustainable pipeline for industry-ready graduates

Currently located in Penang, the CREST office is within 20km radius of at least 3,000 researchers. Inline with the country’s Economic Transformation Programme (ETP), CREST will accelerate economic growth by being the platform for Industry and Academia to collaborate in research, design and development activities.

CREST’s 15 Founding Members include 11 leading E&E companies namely Advanced Micro Devices (AMD), Altera, Avago Technologies, Bose, Clarion, Intel, Keysight Technologies, Motorola Solutions, National Instruments, OSRAM Opto Semiconductors, and SilTerra; together with the Northern Corridor Implementation Authority (NCIA), Khazanah Nasional, University of Malaya (UM), and University of Science Malaysia (USM).

The 11 E&E companies account for more than RM25 billion in total revenue and more than RM1.4 billion in R&D expenditure, as well as employing more than 5000 R&D employees for the sector.