OPENDOTS: A Survey and Problem Study on Intelligent IoT Data Visualization Platforms

Abstract

OpenDots presents a survey-driven study of current challenges in real­time sensor data visualization and interpretation within Internet of Things (IoT) ecosystems. Existing IoT dashboards are widely used for data collection and plot­ting; however, they often suffer from fragmentation, limited customization, and a lack of meaningful interpretability beyond raw visualizations. As IoT deploy­ments scale, users are increasingly required to manually analyze large volumes of time-series data, leading to higher cognitive load and reduced decision effi­ciency. This paper analyzes commonly used IoT visualization platforms and identifies key gaps related to explainability, accessibility, and intelligent data in­teraction. Based on these observations, the paper outlines the problem space mo­tivating the need for unified, web-based platforms capable of supporting real­time data access, controlled sharing, and high-level analytical assistance. A brief conceptual overview of OpenDots is presented to illustrate a possible research direction toward addressing these challenges, without delving into system design or implementation details. The study aims to serve as a foundational reference for future research on intelligent, user-centric IoT data analytics platforms.