Melanie Ooi

Bio: Melanie Ooi is an academic researcher from University of Waikato. The author has contributed to research in topics: Engineering education & Instrumentation (computer programming). The author has an hindex of 2, co-authored 4 publications receiving 15 citations. Previous affiliations of Melanie Ooi include Unitec Institute of Technology & Monash University.

Impact of circadian tuning on the illuminance and color uniformity of a multichannel luminaire with spatially optimized LED placement.

Abstract: Potential advantages offered by multichannel luminaires with regards to spectral tuning are frequently overshadowed by its design challenges, a major one being the non-uniformity in illuminance and color distribution. In this paper, we present a formulation using genetic algorithm (GA) to optimize the Light Emitting Diode (LED) placement, yielding 40% superior uniformity in illuminance and color distributions compared to existing analytical formulations, substantially reducing the reliance on optical design for this purpose. It is specifically shown that our approach is employable for circadian tuning applications, even when heavily constrained by industry specifications on panel size and minimum LED separation.

Roadmap on signal processing for next generation measurement systems

Abstract: Signal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, images, and video sequences comprise representative forms of signals that can be enhanced and analysed for information extraction and quantification. The recent advances in artificial intelligence and machine learning are shifting the research attention towards intelligent, data-driven, signal processing. This roadmap presents a critical overview of the state-of-the-art methods and applications aiming to highlight future challenges and research opportunities towards next generation measurement systems. It covers a broad spectrum of topics ranging from basic to industrial research, organized in concise thematic sections that reflect the trends and the impacts of current and future developments per research field. Furthermore, it offers guidance to researchers and funding agencies in identifying new prospects.

Addressing Emerging Needs of Hi-Tech Industry: Collaborative Engineering Program in Electronic Testing, Instrumentation and Measurement

Abstract: IEEE Region 10 is home to some of the world’s largest semiconductor design and manufacturing facilities. Electronic testing is a branch of a wide instrumentation and measurement field. It plays a key role in verifying and improving quality and functionality of the fabricated integrated circuits as well as in refining the manufacturing process so to reach a required high yield. However, the continuing shortage of qualified engineers in the test, failure analysis, instrumentation and measurement areas in the electronic industry and associated R&D organizations, makes it hard to cover the required production operations. Addressing the need, an integrated specialist education program in the Electronic Test Technology was developed and implemented by a team of university academics in cooperation and with support from management and engineering specialists of several leading electronic companies. The program was also sponsored by the IEEE Instrumentation and Measurement Society Faculty Course Development Award. The paper presents the summary of the developed contents of the teaching and training components. It also outlines the designed laboratory systems, and provides the feedback received from the students and industry.

Virtual Instrumentation Based IC Parametric Tester for Engineering Education

Abstract: Importance of training in electronic test technology within a wider electronic education framework has been acknowledged and extensively discussed in the literature. The main difficulty in incorporating test technology education and training into a curriculum of an electronic engineering degree offered by higher education institutions is an extremely high cost of industry-grate automated test equipment. Trying to address this shortcoming, this paper proposes a fully operational prototype of a simple low-cost programmable electronic test system for functional and DC parametric testing of simple logic ICs. The system is based on National Instruments tools and software. It has been developed to aid teaching of undergraduate units ECE4064 Electronic Test Technology offered at Monash University, Malaysia and 143 .457 Advanced Micro Technologies offered at Massey University, New Zealand.

The Spectral Optimization of a Commercializable Multi-Channel LED Panel With Circadian Impact

Abstract: There exists a need for the design of light emitting diode (LED) luminaires which can deliver both visual and non-visual benefits of light to humans. In this work, we introduce an optimization approach based on spectral shaping for a minimalistic and practical design of a circadian-tunable multi-channel luminaire which also outputs white light with high quality and luminous efficacy of radiation (LER). The spectral optimization approach utilizes Multi-objective Genetic Algorithm to maximize circadian tunability, light quality and LER while minimizing the number of channels. Solution sets are constrained using the non-visual quality metric, Melanopic Efficacy of Luminous Radiation (MELR) from the Melanopic Equivalent Daylight Illuminance (MEDI) approach and the more stringent visual quality metric TM-30 in addition to conventional Color Rendering Index (CRI). By matching theoretically optimized LED parameters to commercially available LED parameters for commercialization purposes, we establish the maximum MELR tunability that is achievable with 4 and 5 LED channels and the resulting trade-off in efficacy and light quality. Based on the results and analysis in this work, we detail a spectral optimization approach to propel the field of indoor lighting towards human-centric lighting.

Indoor lighting design for healthier workplaces: natural and electric light assessment for suitable circadian stimulus

Abstract: Light, especially daylight, plays a critical role in human health as the main timer for circadian rhythms. Indoor environments usually lack the correct exposure to daylight and are highly dependent on electric lighting, disrupting the circadian rhythm and compromising the health of occupants. The methodology proposed assesses the combination of natural and electric lighting on circadian rhythms for operational environments. The case study chosen examines a 24/7 laboratory area representing an open-plan shift-work area. Several electric lighting scenarios under different sky conditions have been assessed, considering a variable window size and resulting in a spectrum which establishes the indoor circadian regulation performance according to the amount of light perceived. A set of configurations is presented to determine optimal electric lighting configuration based on natural light conditions in order to ensure a suitable circadian stimulus and the electric lighting flux threshold for different scenarios, benefiting occupants’ health while also ensuring energy conservation.

Melanopic Limits of Metamer Spectral Optimisation in Multi-Channel Smart Lighting Systems

Abstract: Modern indoor lighting faces the challenge of finding an appropriate balance between energy consumption, legal requirements, visual performance, and the circadian effectiveness of a spectrum. Multi-channel LED luminaires have the option of keeping image-forming metrics steady while varying the melanopic radiance through metamer spectra for non-visual purposes. Here, we propose the theoretical concept of an automated smart lighting system that is designed to satisfy the user’s visual preference through neural networks while triggering the non-visual pathway via metamers. To quantify the melanopic limits of metamers at a steady chromaticity point, we have used 561 chromaticity coordinates along the Planckian locus (2700 K to 7443 K, ±Duv 0 to 0.048) as optimisation targets and generated the spectra by using a 6-channel, 8-channel, and 11-channel LED combination at three different luminance levels. We have found that in a best-case scenario, the melanopic radiance can be varied up to 65% while keeping the chromaticity coordinates constant (Δu′v′≤7.05×10−5) by using metamer spectra. The highest melanopic metamer contrast can be reached near the Planckian locus between 3292 and 4717 K within a Duv range of −0.009 to 0.006. Additionally, we publish over 1.2 million optimised spectra generated by multichannel LED luminaires as an open-source dataset along with this work.

Machine Learning Methods in Smart Lighting Towards Achieving User Comfort: A Survey

Abstract: Smart lighting has become a universal smart product solution, with global revenues of up to US$5.9 billion by 2021. The technology is driven by six main factors: light-emitting diodes (LED) lighting, sensors, control, analytics, and intelligence. The Internet of things (IoT) concept with the end device, platform, and application layer plays an essential role in optimizing the advantages of LED lighting in the emergence of smart lighting. The ultimate aim of smart lighting research is to introduce low energy efficiency and high user comfort, where the latter is still in the infancy stage. This paper presents a systematic literature review (SLR) from a bird’s eye view covering full-length research topics on smart lighting, including issues, implementation targets, technological solutions, and prospects. In addition to that, this paper also provides a detailed and extensive overview of emerging machine learning techniques as a key solution to overcome complex problems in smart lighting. A comprehensive review of improving user comfort is also presented, such as the methodology and taxonomy of activity recognition as a promising solution and user comfort metrics, including light utilization ratio, unmet comfort ratio, light to comfort ratio, power reduction rate, flickering perception, Kruithof ’s comfort curve, correlated color temperature, and relative mean square error. Finally, an in-depth discussion of open issues and future challenges in increasing user comfort in smart lighting using activity recognition is also provided.