Research topic: AI-based Audio Signal Processing applied in Intelligent Transportation Systems.I have successfully applied different models (including 1D-CNN, 2D-CNN, Few-shot Learning, Transformers, Transfer Learning, and Autoencoders) to the features extracted from raw audio and enhanced the accuracy of the available models by 29%, or increased the accuracy to 98%, on a data collected in real-life settings.The results of the research have been published in Q1 journals. (For more details, please visit the publication section at the end of this page)

Key responsibilities:• Developing code using ITS-Port to extract various types of information from the SCATS software.• Analyzing and mapping data to real-world conditions, collaborating with team experts to share and transfer necessary knowledge.• Designing and implementing Deep Learning-driven predictive algorithms utilizing multi-dimensional data.Achievements• Successfully created code to extract data from SCATS software.• Effectively mapped data and shared essential knowledge with team members.• Achieved over 98% accuracy in prediction tasks through the development and deployment of AI models.

To overcome the limitations of the wired connection, such as time and cost for implementation and maintenance, I developed a secure wireless sensor network based on the latest generation of ZIGBEE wireless protocol.I led the design and implementation of a secure wireless sensor network (WSN) for interconnecting ITS infrastructure at intersections. This network connects various ITS devices, including intelligent traffic controllers and traffic signal heads. The project emphasized user-friendliness by developing flexible hardware and software options, facilitating a streamlined and rapid configuration and installation process. To guarantee compatibility with existing intelligent traffic controllers, the network incorporates a unique set of adjustable features for each transmitter/receiver module. This innovative approach not only resulted in significant cost reductions for linking infrastructure but also led to a substantial decrease in maintenance and installation times by at least 70%.

I have applied a wide range of AI methods using tools like KNIME, MATLAB, Python, and R to analyze traffic data. Notable projects in this domain include:- The Impact of Traffic Equipment on Accident Rates: Investigating the correlation between intelligent traffic controllers and accident reduction.- Traffic Accident Estimation Based on Temporal and Dynamic Factors: Estimating the number of accidents based on the static features such as the traffic equipment and roads, and dynamic features such as weather and traffic volume at different regions of the city.- Predicting the Place and Type of Next Accident: Developing models to anticipate the location and nature of future accidents, based on static and dynamic features.- Anomaly Detection in Traffic Flow using Topic Modeling: Employing topic modeling techniques to identify abnormal patterns in traffic flow.- Travel Time Prediction: Utilizing deep learning models to predict travel times.I have also cooperated on other projects as an electronic engineer using my expertise in digital design, complex algorithm design, and code design and implementation. Additionally, I have conducted research focused on the development and application of AI models for a hierarchical network of Intelligent Traffic Controllers. As a project management consultant, I have provided valuable insights and guidance in projects in this field.

Promoted to R&D supervisor. Notable accomplishments include:- Over Speed Detection: Successfully implemented an Over Speed Detection system. (For more detailed information and images of the project, please visit: https://github.com/parineh/RADAR/wiki )- Red Light Violation Enforcement System: Introduced Iran's first system for red-light violation enforcement system, (For more detailed information and images of the project, please visit: https://github.com/parineh/RedLightEnf/wiki ).- Emergency Lane Violation Detection in Tunnels: Led the design and implementation of the emergency lane violation detection system for tunnels. (For more detailed information and images of the project, please visit: https://github.com/parineh/TunnelEmergencyLane/wiki )- Lane Change Detection in Tunnels: Led a lane change detection system for tunnels. (For more detailed information and images of the project, please visit my portfolio page:https://github.com/parineh/TunnelLaneChange/wiki )- SCATS Network Setup: Setup SCATS network and produced a user-guide on setting up a SCATS network for hardware tests and setup before field implementation. (For more detailed information and images of the project, please visit: https://github.com/parineh/SCATS_Connection/wiki )- RADAR and IP-based Digital Camera Integration: Designed and implemented a heuristic method for mapping RADAR (2D data) to IP-based digital camera (3D data). Engaging in these projects has enhanced my knowledge and elevated my skills and expertise in engineering, research, and development. I enjoy innovation, delivering exceptional results, and contributing to complex projects.

Designing and implementation of hardware and micro-controller software for over 30 successful projects.