International Conference on Sensing Technology

NexAIoT to Launch Next-Gen AI-Powered AMR NexMOV-2 with Kudan Visual SLAM and Showcase at Japan Robot Week 2024 Kudan Inc. (Headquarters: Shibuya-ku, Tokyo; CEO: Daiu Ko) is excited to announce the commercial launch of the NexMOV-2, a next-generation AI-powered autonomous mobile robot developed by NexAIoT Co., Ltd. (Headquarters: New Taipei City, Taiwan; Chairman: Clement Lin). NexAIoT, a leader in industrial automation solutions, has equipped the NexMOV-2 with Kudan’s cutting-edge Visual SLAM technology, providing groundbreaking navigation capabilities for industries seeking high-performance, autonomous solutions. NexAIoT’s development of the NexMOV-2 focused on creating an advanced autonomous mobile robot (AMR) that leverages its in-house AI and hardware expertise. By integrating Kudan Visual SLAM, the NexMOV-2 is designed for versatile deployment across a variety of environments while significantly reducing the production costs of AMRs. This strategic partnership between NexAIoT an

Physicists find superconductor behavior at temperatures once thought 'impossible' Scientists have observed an unexpected new behavior in a superconducting material. If physicists can figure out the cause, it could help them to find room-temperature superconductors. An artist's concept image of a levitating superconductor. (Image credit: ktsimage via Getty Images) Scientists have found a key process required for superconductivity occurring at higher temperatures than previously thought. It could be a small but significant step in the search for one of the "holy grails" of physics, a superconductor that operates at room temperature. The discovery, made inside the unlikely material of an electrical insulator, reveals electrons pairing up at temperatures of up to minus 190 degrees Fahrenheit (minus 123 degrees Celsius) — one of the secret ingredients to the near-lossless flow of electricity in extremely cold superconducting materials. So far, the physicists are baf

  Intelligent Condition Monitoring refers to the advanced process of continuously assessing the operational health and performance of machinery and systems using a combination of modern technologies, data analytics, and artificial intelligence. This approach enables the early detection of potential failures, optimization of maintenance schedules, and overall enhancement of operational efficiency. Key Components: Data Acquisition : Utilizes various sensors and data sources (e.g., temperature, vibration, pressure) to collect real-time information on machinery conditions. Multimodal Signals : Involves analyzing multiple types of signals (e.g., acoustic, thermal, and vibration) to obtain a comprehensive view of the equipment's health. Data Processing and Analysis : Employs advanced algorithms and machine learning techniques to process and analyze the collected data, identifying patterns and anomalies indicative of potential issues. Hybrid Models : Combines different modeling approache