A study in Smart Agricultural Technology explores AI and IoT integration to optimize hydroponic crop growth, enhancing efficiency and sustainability. By employing machine learning and real-time data from IoT sensors, researchers achieved precise crop recommendations and environmental control, significantly improving hydroponic farming outcomes.
A recent study in Robotics introduced an intelligent hybrid task planner for multi-robot disassembly of electric vehicle (EV) lithium-ion batteries. This system, tested with various trajectory-planning algorithms, demonstrated efficient and adaptable collaboration between robots, streamlining the battery recycling process and highlighting its potential for broader disassembly tasks in the circular economy.
Researchers investigated the energy consumption of the Printing Mantis, a robot designed for 3D concrete printing (3DCP), by developing a novel energy consumption model. Their study revealed that optimizing the robot's kinematic structure and considering actuator efficiency are crucial for reducing energy usage, achieving a prediction accuracy of up to 90.3%, thus paving the way for more efficient 3DCP applications.
A recent study in Nature Communications reveals rapid changes in the nuclear structure and crystal field of a manganese-based single-molecule magnet using ultrafast X-Ray spectroscopy, highlighting the potential for light-regulated magnetization.
Researchers developed a cost-effective robotic camera system to capture images of greenhouse plants, enhancing plant growth monitoring and data analysis for precision agriculture. The system demonstrated high accuracy in plant identification, movement, and image quality, showcasing its potential to revolutionize agricultural practices.