[Paper Review] Indoor Location for Smart Environments with Wireless Sensor and Actuator Networks

Zhongliang Zhao, Stephane Kuendig+4 more|arXiv (Cornell University)|May 26, 2017

Indoor and Outdoor Localization Technologies11 references3 citations

TL;DR

Smart Syndesi proposes an integrated indoor location-aware system using wireless sensor and actuator networks (WSANs) to enable real-time occupant tracking and automated environmental control in smart buildings. By leveraging smartphone-based indoor positioning, the system triggers context-aware automation of lighting and ventilation based on user location and sensor data, achieving accurate, real-time environmental adaptation in office environments.

ABSTRACT

Smart environments interconnect indoor building environments, indoor wireless sensor and actuator networks, smartphones, and human together to provide smart infrastructure management and intelligent user experiences. To enable the "smart" operations, a complete set of hardware and software components are required. In this work, we present Smart Syndesi, a system for creating indoor location-aware smart building environments using wireless sensor and actuator networks (WSANs). Smart Syndesi includes an indoor tracking system, a WSAN for indoor environmental monitoring and activation automation, and a gateway interconnecting WSAN, tracking system with mobile users.The indoor positioning system tracks the real-time location of occupants with high accuracy, which works as a basis for indoor location-based sensor actuation automation.To show how the multiple software/hardware components are integrated, we implemented the system prototype and performed intensive experiments in indoor office environments to automate the indoor location-driven environmental sensor monitoring and activation process. The tracked indoor location of a user's smartphone triggers the retrieval of environmental measurements and activates the actuators automatically (i.e. turn on/off lights, switch on/off fans) based on the location and correlated environmental sensor information.

Motivation & Objective

• To develop an integrated system that enables real-time indoor location tracking for smart building automation.
• To address the challenge of automating environmental actuation based on occupant location and real-time sensor data.
• To design a gateway system that seamlessly connects wireless sensor and actuator networks with mobile user tracking systems.
• To demonstrate the feasibility and accuracy of location-driven environmental control in real office environments.

Proposed method

• The system employs a wireless sensor and actuator network (WSAN) to monitor indoor environmental conditions such as light and temperature.
• An indoor tracking system uses smartphone-based positioning to determine the real-time location of occupants with high accuracy.
• A centralized gateway integrates the WSAN, tracking system, and mobile users to enable data exchange and control signaling.
• Environmental actuation—such as turning lights or fans on/off—is triggered automatically based on the user's tracked location and correlated sensor readings.
• The system uses proximity-based logic to map user location to specific environmental control actions in designated zones.
• Prototypes were deployed and tested in real indoor office environments to evaluate performance and integration.

Experimental results

Research questions

• RQ1 How can indoor location tracking be effectively integrated with wireless sensor and actuator networks for smart building automation?
• RQ2 What level of accuracy can be achieved in real-time occupant localization using smartphone-based systems in office environments?
• RQ3 How can environmental actuation be automated based on real-time user location and sensor data?
• RQ4 What is the performance of a gateway system in unifying WSAN, tracking, and mobile user data flows?
• RQ5 How does the system maintain responsiveness and reliability in dynamic indoor settings?

Key findings

• The system achieved high-accuracy real-time indoor tracking of occupants using smartphone-based positioning, enabling precise location-aware automation.
• Environmental actuation, such as lighting and fan control, was successfully triggered based on user location and sensor data, demonstrating context-aware responsiveness.
• The gateway system effectively unified communication between the WSAN, tracking system, and mobile users, ensuring low-latency control signals.
• The prototype demonstrated reliable and consistent automation in real office environments, validating the feasibility of the integrated approach.
• The system enabled dynamic adaptation of environmental settings based on occupant presence and location, improving energy efficiency and user experience.