This thesis explores the simulation and validation of Temporal Neural Networks (TNNs), a form of Artificial Neural Network (ANN) which is relatively underdeveloped, presenting opportunities for further exploration and innovation. TNNs are an interesting research topic, because they attempt to mimic the way biological neural networks process information, relying on temporal pulses or spikes rather than continuous activation. Past works have developed simulators for Temporal Neural Network (TNN) systems, but these simulators often face significant limitations due to the environments in which they are implemented. The primary challenge lies in their inefficiency, which makes conducting large-scale tests difficult. This gives the research question of this thesis is: Can a simulator be developed in an environment that would enable large-scale experimentation and testing of TNN systems? This thesis presents a compiled code event driven simulator for TNN systems, with results for a pre-trained network matching past work, as well as preliminary results for reinforcement learning using TNN systems.

Augmented Reality has the potential to expand our interaction with our surrounding environment. A potential solution to improve this interactability is Visible Light Communication through blinking Light Emitting Diodes (LEDs). Data is encoded and then transmitted by blinking the LED, a smart-phone camera is then pointed at the LED to decode the message from the blinking light. The light must blink at a high enough frequency, otherwise the blinking LED causes flicker which has negative health risks. In this research, an experiment is conducted to check the viability of this technology, by transmitting a message to multiple phones with different recording frame rates and checking whether the technology functions adequately for each frame rate. The viability is checked through multiple factors, with the most important one being flicker, due to the negative health risks. If there is no flicker, the throughput of the LED at that frame rate and blinking frequency is checked at multiple distances. The results show that only the highest recording frame rate used in the experiment is viable and that the ones below all cause flicker. This makes it hard to consider the technology viable, due to it only functioning on a limited amount of smartphones.