Face Recognition Based Multifunction IoT Smart Mailbox

The abundance and variety of the Internet of Things (IoT) applications in the recent couple of years has reach a new record. From smart home, smart traffic, smart city, to industry, logistics and agriculture IoT applications are penetrating in every facet of our life and our society. A lot of simple and more complicated solutions benefit from the flexibility and diversity of connections that this new technology provides. In order to provide better management, better visualization, increase scale and reduce response times logistics and warehouse management are embracing new ways to improve upon the already “old” RFID technology. In this sense IoT provides an unprecedented technology to meet all these requirements in a uniform and easy to manage way. In this work a specific smart application – IoT mailbox with face recognition is discussed. Combining cellular connectivity with image processing it ensures the user that his valuable documents will be securely delivered. The developed prototype consists of a fingerprint reader, a camera, electromagnetic lock, a small LCD screen, a microphone and a loudspeaker all connected to an Arduino Uno which processes the data and establishes the network connectivity through a GSM module. Additionally, to perform face detection and recognition based on a prerecorded image set the camera is connected to Raspberry Pi and OpenCV and Python software is employed. The remotely controlled electromagnetic lock ensures that shipments are kept protected until the designated receiver takes possession of them.

Face Recognition Based Multifunction IoT Smart Mailbox

The abundance and variety of the Internet of Things (IoT) applications in the recent couple of years has reach a new record. From smart home, smart traffic, smart city, to industry, logistics and agriculture IoT applications are penetrating in every facet of our life and our society. A lot of simple and more complicated solutions benefit from the flexibility and diversity of connections that this new technology provides. In order to provide better management, better visualization, increase scale and reduce response times logistics and warehouse management are embracing new ways to improve upon the already “old” RFID technology. In this sense IoT provides an unprecedented technology to meet all these requirements in a uniform and easy to manage way. In this work a specific smart application – IoT mailbox with face recognition is discussed. Combining cellular connectivity with image processing it ensures the user that his valuable documents will be securely delivered. The developed prototype consists of a fingerprint reader, a camera, electromagnetic lock, a small LCD screen, a microphone and a loudspeaker all connected to an Arduino Uno which processes the data and establishes the network connectivity through a GSM module. Additionally, to perform face detection and recognition based on a prerecorded image set the camera is connected to Raspberry Pi and OpenCV and Python software is employed. The remotely controlled electromagnetic lock ensures that shipments are kept protected until the designated receiver takes possession of them.

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  • S. N Shukla, T.A. Champaneria, “Survey of various data collection ways for smart transportation domain of smart city”, 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), DOI: 10.1109/I-SMAC.2017.8058265, 2017
  • L. Yaqiong, T. Lei, C. K. M. LEE and T. Xin, "IoT based Omni-Channel Logistics Service in Industry 4.0," 2018 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI), Singapore, 2018, pp. 240-243.
  • M. Glöckner, A. Ludwig and B. Franczyk, "A Reference Architecture for the Logistics Service Map: Structuring and Composing Logistics Services in Logistics Networks," 2016 IEEE International Conference on Computer and Information Technology (CIT), Nadi, 2016, pp. 644-651.
  • J. R. Tew and L. Ray, "ADDSMART: Address digitization and smart mailbox with RFID technology," 2016 IEEE 7th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), New York, NY, 2016, pp. 1-6.
  • A. Muhammad and N. ur Rehman, "Intelligent mailbox with centralized parallel processing," 2016 17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), Shanghai, 2016, pp. 255-259.
  • S. Ze-hong and Z. Guang-yuan, "Multi-functional Parcel Delivery Locker system," 2015 International Conference on Computer and Computational Sciences (ICCCS), Noida, 2015, pp. 207-210.
  • Y. Zhao, J. Gu, C. Liu, S. Han, Y. Gao and Q. Hu, "License Plate Location Based on Haar-Like Cascade Classifiers and Edges," 2010 Second WRI Global Congress on Intelligent Systems, Wuhan, 2010, pp. 102-105.
  • Shiguang Shan, Bo Cao, Wen Gao and Debin Zhao, "Extended Fisherface for face recognition from a single example image per person," 2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353), Phoenix-Scottsdale, AZ, USA, 2002, pp. II-II.
  • M. Johnson and A. Savakis, "Fast L1-eigenfaces for robust face recogntion," 2014 IEEE Western New York Image and Signal Processing Workshop (WNYISPW), Rochester, NY, 2014, pp. 1-5.