Building AI and analytics-based security features for a visibility platform focused on ITDR (Identity Threat Detection and Response)

• Spearheaded the design and development of AI dashcam software, from concept to deployment.

• Engineered real-time event detection mechanisms, enabling the dashcam to identify critical safety events such as overspeeding, harsh braking, swerving, and collisions, and promptly alerting drivers and fleet managers.

• Implemented live streaming functionality using webRTC, allowing users to remotely access and monitor dashcam footage through web and mobile applications in real-time.

• Integrated ADAS and DMS to provide collision alerts, lane departure warnings, and to monitor driver attentiveness, drowsiness, and distractions, thereby enhancing overall road safety.

• Developed scalable backend architecture to handle data processing, storage, and retrieval of dashcam-generated data, ensuring efficient performance and responsiveness.

Data Structures and Algorithms

Machine Learning

Artificial Intelligence

• Designed and developed an end-to-end cloud-based solution for dashboard cameras.

• Built microservices to manage dashcam data and auto-upload event videos.

• Developed a system to analyze data from dashcams and provide real-time alert notifications.

• Set up an Nginx-based streaming service to stream live video from a dashcam in multiple resolutions.

• Developed new features for DITA content authoring and management in Adobe Experience Manager.

• Designed a Lucene indexing mechanism for advanced search using content attributes and metadata.

• Built a desktop plugin to allow users to access the AEM repository directly from the Oxygen XML Editor app.

• Analyzed and resolved performance bottlenecks in key features reducing the response time by upto 70%.