3D printing
Researchers at North Carolina State University have developed a new 3D printing technique that creates paper-thin "magnetic muscles" that can be applied to origami structures to make them move. This innovation has significant potential in robotics, particularly in areas like biomedicine and space exploration. Key Takeaways: * The new
Sensors
Researchers at Universitat Politecnica de Catalunya have made a significant discovery in the field of sensor and actuator networks. The team has designed a novel Electrowetting-on-Dielectric (EWOD) sensor that can rapidly quantify marine dispersants at the spill point. This innovation offers a crucial tool for effective oil spill response, enabling
Sensors
Researchers from Universitas Muhammadiyah Surakarta have developed a novel dual-battery architecture with intelligent auto-switching control, designed to ensure uninterrupted operation of agricultural sensing systems in environments with unpredictable energy availability. The proposed system integrates Lithium-Sulphur (Li-S) and Lithium-Ion (Li-Ion) batteries with advanced switching algorithms, tailored to maximize sensor operational longevity.
Sensors
Research on the Internet of Drones (IoD) has revealed the growing risk of security breaches due to the transmission of data over unsecured public channels. According to a new study, IoD applications have significant potential in various fields, including military, healthcare, smart agriculture, and traffic monitoring. However, the use of
Sensors
Wuyi University researchers have made a breakthrough in sensor and actuator networks with the development of a two-stage cooperative strategy that leverages Gaussian Processes and Twin Delayed Deep Deterministic Policy Gradient (TD3) for policy optimization. The innovative approach aims to enhance adaptability and multi-objective optimization in mobile multi-agent systems, where
Sensors
Researchers from Yeungnam University in South Korea have made significant progress in developing an innovative method for identifying human movement direction in indoor environments using low-resolution time-of-flight (ToF) sensors and long short-term memory (LSTM) neural networks. This breakthrough has the potential to revolutionize various applications, including surveillance, navigation, and human-computer
