Daniel Vaquerizo-Hdez

Papers

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About

Daniel Vaquerizo-Hdez is a researcher focused on energy-efficient wireless sensor networks (WSNs) and AI-driven teleassistance systems for smart environments. His major contributions lie in developing low-power communication protocols and intelligent monitoring frameworks that enhance the autonomy and responsiveness of embedded systems. His most cited work, "A Low Power Consumption Algorithm for Efficient Energy Consumption in ZigBee Motes" (2017, 17 citations), introduces an algorithm that significantly reduces energy usage in ZigBee-based motes, enabling longer-lasting, wire-free deployments critical for applications in robotics, telecare, domotics, and smart cities. Building on this, his paper "LARES: An AI-based teleassistance system for emergency home monitoring" (2019, 15 citations) presents an integrated system that leverages artificial intelligence to detect and respond to emergencies in home environments, demonstrating the practical impact of combining low-power sensing with intelligent decision-making. Vaquerizo-Hdez’s work bridges the gap between energy-efficient hardware design and real-world AI applications, offering scalable solutions for next-generation ambient assisted living and urban infrastructure.