Review of methods and technologies to detect, count and identify people in indoor environments
The rapid advancement of technology has significantly improved the methods for identifying and counting individuals in indoor environments. This paper presents a systematic review of existing non-intrusive methods and technologies used for indoor detection, counting and identification of people. The review evaluates relevant literature, identifying key technologies that provide accurate detection and practical applications across various domains. The methods are categorized into six groups based on the evaluated parameters: Acoustic-based, Biometric-based, Body Indices-based, Gait-based, Infrared-based, and Smart Device-based. This categorization helps understand each method’s strengths and weaknesses, facilitating future research and development in this field.
Authors
- Sara Comai (ORCID: https://orcid.org/0000-0002-9554-8815)
- Andrea Masciadri (ORCID: https://orcid.org/0000-0001-7623-9382)
- Fabio Salice (ORCID: https://orcid.org/0000-0002-0434-0446)
- Gabriele Maria Stabile
- Enrico Vavassori
- Matteo Zerilli
Institutions
- Politecnico di Milano (IT)
Publication Details
- Journal
- Internet of Things
- Published
- 2024-12-21
- DOI
- https://doi.org/10.1016/j.iot.2024.101466
- Citations
- 4
- Primary Topic
- IoT-based Smart Home Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.83