EMBEDDED POWER ACTIVE CONTACT LENS

This thesis designed and fabricated an active contact lens that notifies the user during the detection of an external wireless signal. The lens contained a printed antenna to communicate with a 2.4GHz system and provide inductive charging operating at 13.56 MHz. The lens utilizes a CBC005 5µAh thin film battery by Cymbet as a power source. A custom IC was designed using the On Semiconductor CMOS C5 0.6 µm process to manage the battery and drive the display. A printed single element display using electrochromic ink was chosen as it is able to indicate the user when activated while staying transparent. Lastly, this thesis analyzes the material properties of the chosen substrate for it clearness, flexibility, and biocompatibility to determine its suitability as a contact lens material

Clear Circuit Contact Lens

The clear active contact lens project aims to address safety and hazard awareness with an unexplored field of eye wear technology. With advancements in nanotechnology and the advent of circuits on contact lens, this project is one of the first research and development into this new field, following University of Washington and Google. The team focuses on the safety and biocompatibility of the contact lens for a comfortable ease of use. The designs push the limits of thin film printed technology with its pursuit of fine designs of 250μm antennas. The project streamlines the manufacturing process for a combination substrate of PET and PDMS and mounting of antenna, IC, and battery. To produce a product that operates at simulated specifications, the team tests and characterize the substrate, antenna, IC, and battery separately, while ensuring their designs function effectively together. The designs and processes provide a large stepping stone to the realization of a marketable active contact lens

Minimizing Electricity Cost through Smart Lighting Control for Indoor Plant Factories

Smart plant factories incorporate sensing technology, actuators and control algorithms to automate processes, reducing the cost of production while improving crop yield many times over that of traditional farms. This paper investigates the growth of lettuce (Lactuca Sativa) in a smart farming setup when exposed to red and blue light-emitting diode (LED) horticulture lighting. An image segmentation method based on K-means clustering is used to identify the size of the plant at each stage of growth, and the growth of the plant modelled in a feed forward network. Finally, an optimization algorithm based on the plant growth model is proposed to find the optimal lighting schedule for growing lettuce with respect to dynamic electricity pricing. Genetic algorithm was utilized to find solutions to the optimization problem. When compared to a baseline in a simulation setting, the schedules proposed by the genetic algorithm can achieved between 40-52% savings in energy costs, and up to a 6% increase in leaf area.Comment: IEEE IECON 202

Implementation of the compulsory universal testing scheme in Hong Kong: Mathematical simulations of a household-based pooling approach

This study aims to propose a pooling approach to simulate the compulsory universal RT-PCR test in Hong Kong and explore the feasibility of implementing the pooling method on a household basis. The mathematical model is initially verified, and then the simulation is performed under different prevalence rates and pooled sizes. The simulated population is based in Hong Kong. The simulation included 10,000,000 swab samples, with a representative distribution of populations in Hong Kong. The samples were grouped into a batch size of 20. If the entire batch is positive, then the group is further divided into an identical group size of 10 for re-testing. Different combinations of mini-group sizes were also investigated. The proposed pooling method was extended to a household basis. A representative from each household is required to perform the RT-PCR test. Results of the simulation replications, indicate a significant reduction (p < 0.001) of 83.62, 64.18, and 48.46% in the testing volume for prevalence rate 1, 3, and 5%, respectively. Combined with the household-based pooling approach, the total number of RT-PCR is 437,304, 956,133, and 1,375,795 for prevalence rates 1, 3, and 5%, respectively. The household-based pooling strategy showed efficiency when the prevalence rates in the population were low. This pooling strategy can rapidly screen people in high-risk groups for COVID-19 infections and quarantine those who test positive, even when time and resources for testing are limited

Local human movement patterns and land use impact exposure to zoonotic malaria in Malaysian Borneo.

Human movement into insect vector and wildlife reservoir habitats determines zoonotic disease risks; however, few data are available to quantify the impact of land use on pathogen transmission. Here, we utilise GPS tracking devices and novel applications of ecological methods to develop fine-scale models of human space use relative to land cover to assess exposure to the zoonotic malaria Plasmodium knowlesi in Malaysian Borneo. Combining data with spatially explicit models of mosquito biting rates, we demonstrate the role of individual heterogeneities in local space use in disease exposure. At a community level, our data indicate that areas close to both secondary forest and houses have the highest probability of human P. knowlesi exposure, providing quantitative evidence for the importance of ecotones. Despite higher biting rates in forests, incorporating human movement and space use into exposure estimates illustrates the importance of intensified interactions between pathogens, insect vectors and people around habitat edges