Looping during colonoscopy procedures is a major cause of patient discomfort and increases the risk of complications. With the rising incidence of colorectal cancer, there is an urgent need for safer and more efficient colonoscopy techniques. We developed a proof-of-concept platform for 3D visualization of the colonoscope combined with artificial intelligence (AI)-based loop detection. The system consists of an array of 15 inertial measurement units (IMUs) mounted on a flexible printed circuit board that can be retrofitted into the instrument channel of conventional colonoscopes. Using sensor fusion algorithms, the position and orientation of individual IMUs are estimated to reconstruct the 3D shape of the colonoscope in real time. The system successfully reconstructed the colonoscope shape in a silicone colon phantom, and the AI model achieved high loop-detection performance with an area under the receiver operating characteristic curve of 0.95 on test data. These results demonstrate feasibility in an artificial environment, while further validation in clinical settings is required.