ABSTRACT
A new magnetic molecular imprinting-based turn-on fluorescence probe (Fe3 O4 NPs@SiO2 @NBD@MIPs) has been synthesized via a facile sol-gel polymerization for the detection of 2,4-dichlorophenoxyacetic acid (2,4-D). Based on the photoinduced electron transfer (PET) of nitrobenzoxadiazole (NBD), 2,4-D can be recognized by enhancement of NBD fluorescence. With the presence of Fe3 O4 in the core of the probe, this sensor can also be reused many times using magnetic aggregation methods. After the addition of various concentrations of 2,4-D, the fluorescence peak at 530 nm (excitation of 468 nm) increased linearly ranging from 0.1 to 3 µM with a detection limit of 0.023 µM. This sensing system is believed to be available for detecting 2,4-D in real samples, with high recovery rates ranging from 94% to 108% for three spike levels of 2,4-D with precisions below 5%.
ABSTRACT
This paper presents a gesture-controlled robotic arm system designed for agricultural harvesting, utilizing a data glove equipped with bending sensors and OptiTrack systems. The system aims to address the challenges of labor-intensive fruit harvesting by providing a user-friendly and efficient solution. The data glove captures hand gestures and movements using bending sensors and reflective markers, while the OptiTrack system ensures high-precision spatial tracking. Machine learning algorithms, specifically a CNN+BiLSTM model, are employed to accurately recognize hand gestures and control the robotic arm. Experimental results demonstrate the system's high precision in replicating hand movements, with a Euclidean Distance of 0.0131 m and a Root Mean Square Error (RMSE) of 0.0095 m, in addition to robust gesture recognition accuracy, with an overall accuracy of 96.43%. This hybrid approach combines the adaptability and speed of semi-automated systems with the precision and usability of fully automated systems, offering a promising solution for sustainable and labor-efficient agricultural practices.