Navistar – A universal IoT platform for smart systems
Main Article Content
Abstract
Recent years have seen a rapid development of AI-based IoT systems and applications like real-time object detection systems, face identification, AI-based cameras, etc. Many of these utilize a compact-form computing device based on SoC embedded modules from different providers like Qualcomm, Renesas, Quectel, etc. One of the most popular and easy-to-access platforms both practically and academically is the Raspberry Pi computing device and other PI-like devices such as: Orange Pi, Banana Pi, Jetson Nano, etc. However, we realize that the existing platforms strongly focus on the computation aspect, while other important features such as communication, location, ease of integration with high-level operating systems are lacking or poorly supported (through the use of so-called HAT). Therefore, in this work we propose a design of a multi-purpose IoT platform with full integration of computation module, IO ports, communications, location and high-level operating system (Android). We also utilize this IoT platform in a variety of applications including data collection, location-based services and biometric identification. Those sample applications will be presented in our work together with the algorithm and testing result to demonstrate the practical use of our platform.
Keywords
IoT, AI, Single board computer, Smart SoC
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
References
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[3] P. Amruthavarshini, C. V. Raghu, and G. Jagadanand. Development of an IoT enabled smart projection system for classroom needs. 2022 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT). IEEE, 2022. https://doi.org/10.1109/IAICT55358.2022.9887528
[4] Godinho, António, et al. IoT single board computer to replace a home server. 2023 18th Iberian Conference on Information Systems and Technologies (CISTI). IEEE, 2023. https://doi.org/10.23919/CISTI58278.2023.10212031
[5] Ali, Omer, et al. A comprehensive review of internet of things: Technology stack, middlewares, and fog/edge computing interface. Sensors 22.3 (2022): 995. https://doi.org/10.3390/s22030995
[6] Guha, S., Chakrabarti, A., Biswas, S., & Banerjee, S. (2020, December). Implementation of Face Recognition Algorithm on a Mobile Single Board Computer for IoT Applications. In 2020 IEEE 17th India Council International Conference (INDICON) (pp. 1-5). IEEE.
[7] Mikhaylevskiy, S., et al. Fast emotion recognition neural network for IoT devices. 2021 International Seminar on Electron Devices Design and Production (SED). IEEE, 2021. https://doi.org/10.1109/SED51197.2021.9444517
[8] Sruthy, S., and Sudhish N. George. Wifi enabled home security surveillance system using Raspberry Pi and IoT module. 2017 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES). IEEE, 2017. https://doi.org/10.1109/SPICES.2017.8091320 [9] Galkin, Pavlo, Lydmila Golovkina, and Igor Klyuchnyk. Analysis of single-board computers for IoT and IIoT solutions in embedded control systems. 2018 International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T). IEEE, 2018. https://doi.org/10.1109/INFOCOMMST.2018.8632069
[10] Twinn, Gary. Combining low-cost single board computers with open-source software to control noble gas extraction lines. MethodsX 10 (2023): 101974. https://doi.org/10.1016/j.mex.2022.101974