A Smart Enteral Feeding System Using Artificial Intelligence of Things for Efficient Nutrition Delivery
Keywords:Enteral Feeding, Artificial Intelligence, Nutrition, Feeding tube, Mouth Detection.
This research introduced a smart enteral feeding system, employing Artificial Intelligence of Things (AIoT) principles for autonomous nutrition delivery. The system was developed and simulated utilizing an Arduino Uno, motor shield, system camera module, and a precisely calibrated pump motor, targets the enhancement of patient care by responding to cues of hunger detected through mouth opening. Upon mouth detection, the system triggers the precise administration of necessary food substances via a submersible water pump, deactivating seamlessly upon mouth closure. Rigorous testing determined the system's accuracy and automated feeding functionality, showcasing its potential for aiding healthcare workers and patient relatives in providing essential nutrition even in their absence. The developed system underwent thorough testing, demonstrating precise functionality. The system autonomously administered the necessary food substances to the patient. This Research’s innovative AIoT-driven enteral feeding system presented a promising leap in healthcare technology, showcasing precise, autonomous nutrition delivery based on mouth detection cues, building upon and expanding the advancements seen in IoT-enabled healthcare systems. The research recommends further exploration into real-world implementation, advanced sensor technologies, remote monitoring capabilities, improved user interfaces, and rigorous reliability testing to augment the system's efficiency and widespread application in healthcare settings.