Real-time navigation is an intriguing and multifaceted field encompassing numerous intricately weaved technologies, including search algorithms, route optimization, road network graph generation, traffic data analysis, and GPS error correction, to name a few. Using the potential of AI and Machine Learning, we have pioneered several areas:
Big data is the backbone of any navigation app. Its accuracy hinges on timely updates, collection, and digitization. For any navigation app to be relevant, the data sets need to be updated, collected, and digitized on a daily basis. We've harnessed the power of AI and ML to develop in-house services that enable us to manage such large volumes of data with no quality leakage and deliver precise, efficient, and reliable solutions.
Here are some use-cases that demonstrate our mastery over AI/ML algorithms:
Deep learning algorithms expedite data insertion by predicting and assigning accurate categories to Points of Interest (POIs). This model is trained on millions of categorized POIs from the TPL database.
Road Extraction from Satellite Images
Deep neural networks automatically extract road information from satellite imagery, enabling more frequent road network updates compared to traditional manual data collection methods.
Image Text Detection
Advanced Computer Vision algorithms identify and extract video frames containing POI labels from geo-tagged video surveys. These video surveys have locational information, including the POI labels embedded in.
Address Standardization and Validation
TPL Maps is developing an AI/NLP engine to understand the structure and variations of different address types. Application of address standardization and validation techniques will significantly improve the customer engagement process for any business venture.