Convergence of IoT, Financial Analytics, and Image Processing: A Synergistic Framework for Next-Generation Financial Systems
Keywords:
Internet of Things (IoT), Financial Technology (FinTech), Image Processing, Computer Vision, Sensor Fusion, Real-Time Analytics, Risk Assessment, Fraud Detection, Supply Chain Finance.Abstract
Abstract: The unprecedented opportunities presented by the growing data-oriented innovation provided by the rapid digitization of financial services along with the expansion of the Internet of Things (IoT) and computer vision development are emerging. The present article suggests the introduction of a new interdisciplinary model that combines IoT sensor networks, the real-time image processing, and machine learning to transform business operations into financial analytics, risk evaluation, and services provision. We consider the IoT device, smart shelves and connected cars, agricultural drones and industrial sensors that generates the constantly flowing outputs of image and sensor data encoding valuable economic messages. This heterogeneous data can be converted into financial intelligence that can be triggered into action by using sophisticated image processing methods, object detection using deep learning, scene understanding, and anomaly detection. The paper has summarized the information contained in the literature on IoT in healthcare, financial forecasting systems, and computer vision to build a unified vision. Applications studied include: The first application of dynamically valuing collateral positions on real property and inventory images: The model is applicable to the insurance sector where tremendous volumes of damage can be determined by viewing images of the damaged goods and sending them to an automated claims clearing system, as well as fraudulent fraud detection through behavior biometrics and document verification: The second application is predictive analytics used to finance a supply chain: The system should utilize the IoT-enabled visual monitoring of goods. We deal with the considerable technical and ethical issues of such convergence, namely how to guarantee data security and privacy in distributed IoT networks, how to enable processing in real-time at the edge, multimodal data fusion, and liquidity algorithmic bias. The paper will conclude that the IoT, image processing, and financial analytics strategic merger will bring about the creation of more transparent, efficient, and resilient financial architectures, leading to autonomous finance and hyper-personalized services.
