TRACTIAN
Tractian is the Industrial Copilot for maintenance and reliability, combining hardware and software solutions to monitor asset performance, manage industrial operations, and implement predictive maintenance strategies. Its AI-driven platform empowers businesses to prevent unplanned equipment downtime and boost production output. The company is headquartered in Atlanta, GA, and extends its presence globally with offices in Mexico City and Sao Paulo. Learn more at tractian.com.
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RaimaDB
RaimaDB, an embedded time series database that can be used for Edge and IoT devices, can run in-memory. It is a lightweight, secure, and extremely powerful RDBMS. It has been field tested by more than 20 000 developers around the world and has been deployed in excess of 25 000 000 times.
RaimaDB is a high-performance, cross-platform embedded database optimized for mission-critical applications in industries such as IoT and edge computing. Its lightweight design makes it ideal for resource-constrained environments, supporting both in-memory and persistent storage options. RaimaDB offers flexible data modeling, including traditional relational models and direct relationships through network model sets. With ACID-compliant transactions and advanced indexing methods like B+Tree, Hash Table, R-Tree, and AVL-Tree, it ensures data reliability and efficiency. Built for real-time processing, it incorporates multi-version concurrency control (MVCC) and snapshot isolation, making it a robust solution for applications demanding speed and reliability.
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Apollo Autonomous Vehicle Platform
A combination of sensors, including LiDAR, cameras, and radar, gather data from the vehicle's surroundings. By employing sensor fusion technology, perception algorithms are capable of identifying, locating, measuring the speed, and determining the orientation of various objects on the road in real time. This advanced autonomous perception system is supported by Baidu's extensive big data infrastructure and deep learning capabilities, along with a rich repository of labeled real-world driving data. The robust deep-learning platform, complemented by GPU clusters, enhances processing power. Additionally, the simulation environment enables virtual driving across millions of kilometers each day, leveraging diverse real-world traffic and autonomous driving data. Through this simulation service, partners can access an extensive array of autonomous driving scenarios, allowing for rapid testing, validation, and optimization of models in a manner that prioritizes both safety and efficiency, ultimately fostering advancements in autonomous vehicle technology.
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Qualcomm Snapdragon Ride
The Qualcomm® Snapdragon Ride™ Platform stands out as one of the most sophisticated, adaptable, and fully customizable automated driving systems in the automotive sector. It offers automotive manufacturers and suppliers the flexibility to implement the sought-after safety, convenience, and autonomous driving capabilities of today while maintaining the potential for future scalability. This platform boasts dependable, high-performance capabilities tailored for automotive needs, all while ensuring lower power consumption, enhanced simplicity, and greater safety in vehicles. Unlike many other autonomous driving technologies that depend on liquid cooling systems, the Snapdragon Ride Platform utilizes passive or air-cooling methods, making it a more efficient choice. With its unique multi-ECU aggregation feature, this versatile platform can seamlessly transition from active safety measures to convenience features and ultimately to complete self-driving solutions, accommodating a diverse array of vehicles. Furthermore, the Snapdragon Ride Autonomous Stack complements the high-performance, energy-efficient hardware, creating a powerful and sophisticated driving and perception system for vehicles today. This combination positions the platform as a leader in the realm of automotive innovation, paving the way for future advancements in the industry.
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