tracking

Tracking is the process of determining the position, movement, or state of an object over time by collecting observations from sensors or other data sources. It is used across many domains to monitor dynamics, verify conditions, or extract patterns from sequences of events. Tracking can refer to physical movement of tangible entities or the digital trace left by devices and users.

Physical tracking covers vehicles, wildlife, people, and machinery. It can be real-time for navigation and control or retrospective for analysis. Digital tracking covers data trails, device identifiers, and online behavior, including cookies and beacon signals, often across networks and apps.

Techniques rely on a mix of sensing modalities and computational methods. Common sensors include GPS/GNSS, RFID, Bluetooth beacons, Wi‑Fi, cameras with computer vision, lidar, radar, and inertial measurement units. Data are processed with estimation and data-association methods such as Kalman and particle filters, multi-target tracking algorithms, and assignment methods like the Hungarian algorithm.

Applications span logistics and supply chains, transportation, wildlife ecology, sports analytics, healthcare monitoring, security and defense, and marketing. In autonomous systems, tracking supports localization and obstacle tracking. In privacy contexts, tracking can refer to profiling and identification across sites and devices.

Challenges include sensor noise, occlusion, drift, latency, and energy constraints, as well as the complexity of correctly associating observations to targets in crowded scenes. Privacy, consent, and regulatory considerations shape how tracking is implemented and what data are collected.