In 2017, about 144 million people collected water from untreated water bodies, such as lakes, streams, and rivers. One of the major causes of death is consuming contaminated or polluted water. Measuring and monitoring water quality are usually done using two methods. The conventional method occurs by taking samples of water and then transferring them to the laboratory. The second method is real-time water quality by integrating the Internet of Things (IoT). This method is preferable as it only requires smart sensors and processors to monitor the water quality. Among the widely used processors are the Arduino and Raspberry Pi. However, these two processors have a limitation, including a limited number of hard-coded input/output pins, unlike the Field Programmable Gate Array (FPGA) processor, which has many input/output pins not hard-coded to allow different interfacing of multiple sensors. Based on the literature, an FPGA platform provides more flexibility and reconfigurability features when compared with the Arduino and Raspberry Pi. This research mainly focuses on designing a reconfigurable multi-core Smart Water Quality System (SWQS) measuring the pH, Total Dissolved Solids (TDS), and turbidity parameters. The hardware design was developed based on the system-on-chip (SoC) design methodology on an FPGA to parallelize the SWQS functionality. A Liquid-Crystal Display (LCD) display has been incorporated into the Raspberry Pi to show real-time data. The Platform Designer on Quartus II has been used to instantiate four cores to integrate all functions into one processor. The Eclipse tool on Quartus II, on the other hand, was used to program the sensors using embedded C language. The proposed design has been implemented on DE10 Nano FPGA-SoC consuming 9% of logic resources and 57% of internal memory. To verify the proposed system functionality, the sensors were tested on different liquids. To test the pH level, the pH sensor was tested on pure water, lemon juice, and milk to show the acidity and alkalinity. The pH sensor showed 7, less nearly 2, and less than 8 for pure water, lemon juice, and milk, respectively. The TDS sensor successfully detected the salt added to the water, and the TDS values increased to approximately 1800 ppm. Finally, the turbidity sensor revealed the dust inserted in the solution. The more dust in the liquid, the more TDS value there was recorded. Additionally, results showed that the processing time of all the sensors using FPGA is approximately 300 ms for ten readings; on the other hand, the processing time of using other processors, such as Arduino, took 2 s for ten readings. This is because FPGA is functioning at 100 MHz, while Arduino’s frequency is not more than 24 MHz. All real-time sensor readings were shown on a Linux Terminal. In conclusion, the proposed FPGA-based system can be utilized as a heterogeneous multi-core system for many applications, including the SWQS.

One of the objectives and aspirations of scientists and engineers ever since the development of computers has been to interact naturally with machines. Hence features of artificial intelligence (AI) like natural language processing and natural language generation were developed. The field of AI that is thought to be expanding the fastest is interactive conversational systems. Numerous businesses have created various Virtual Personal Assistants (VPAs) using these technologies, including Apple's Siri, Amazon's Alexa, and Google Assistant, among others. While an ongoing effort to increase the friendliness and constancy of informal dialogue systems, most research focuses solely on simulating human-like replies, leaving the features of modeling interlocutors' awareness are unexplored. Meanwhile, cognitive science research reveals that awareness is a crucial indicator of a high-quality informal conversation. To precisely model understanding, Persona Perception (P2) Bot was developed using a transmitter-receiver-based structure. P2 Bot leverages mutual persona perception to improve the quality of customized dialogue generation. Even though many chatbots have been introduced through the years to diagnose or treat psychological disorders, we are yet to have a user-friendly chatbot available. This research aims on improving the quality of conversation generation by implementing the Generative Pre-trained Transformer-2 (GPT-2) model on P2 Bot. GPT-2 is a 1.5B parameter transformer model which produces state-of-the-art accuracy in a zero-shot setting on 7 out of 8 evaluated language modeling datasets. Observations on a large open-source dataset, PERSONA-CHAT, show that the technique is successful, with some improvement above state-of-the-art baselines in both automatic measures and human assessments. The model has achieved 82.2% accuracy on Hits@1(%) in the original data and 68.8% on the revised data. On the human evaluation, the model scored an average of 2.66 meaning the provided responses were coherent and informative. A smart generative cognitive behavioral therapy with spoken dialogue systems support was then developed using the model, which was then implemented using modern technologies in VPAs like voice recognition, Natural Language Understanding (NLU), and text-to-speech. This system is a magnificent device to help with voice-based systems because it can have therapeutic discussions with the users utilizing text and vocal interactive user experience.

Electric vehicles are slowly becoming the first option for consumers. As time passes, the challenges limiting the chances of its existence are being reduced by the efforts of the researchers; they have the idea of having a green world and aim to achieve it by eliminating any source of pollution that found a green replacement. However, how well the performance of electric vehicles is not enough to make an industrial change. While there are challenges yet to be solved additionally, the main problem is the time to fully charge the battery in static and dynamic charging. However, time is rapidly being enhanced for static charging due to the fast charging cable improvements. Still, for dynamic charging, it is all about the efficiency of the connection during the power transmission. In this project, a homogenous coil has been designed, and the main focus is the radius of the coil. The design is tested under different conditions, and the optimal case is when the radius of the transmission coil is bigger than the radius of the receiver coil. The design has recorded an efficiency of up to 95%. Lastly, an enhanced method has been produced to wirelessly charge the electric vehicle with the help of homogeneous pads.