Taoufik Aguili

Tunis El Manar University, Tunis University

Papers

Total Citations

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About

Taoufik Aguili is a leading researcher at the forefront of next-generation networking and intelligent positioning systems. His work spans two critical domains: the Industrial Internet of Things (IIoT) and high-precision indoor localization. Aguili’s most influential contribution, "Toward Self-Adaptive Software Defined Fog Networking Architecture for IIoT and Industry 4.0" (36 citations), proposes a transformative architecture that integrates software-defined networking with fog computing to enable autonomous, adaptive data management for smart factories. This work directly addresses the scalability and latency challenges of connecting billions of IIoT devices. In parallel, Aguili has made significant strides in ultrasonic positioning. His papers "Evaluation of Multi-Sensor Fusion Methods for Ultrasonic Indoor Positioning" (18 citations) and "Characterization of an Ultrasonic Local Positioning System for 3D Measurements" (14 citations) pioneer novel sensor fusion techniques that dramatically improve the accuracy and reliability of indoor navigation for robots and drones in GPS-denied environments. By combining theoretical frameworks with practical system characterizations, Aguili’s research provides foundational blueprints for the autonomous factories and seamless location-based services of tomorrow.