Next-Generation Black Box with IOT and Real Time Monitoring

Authors

  • Sachin Srivastava Department of Aerospace Engineering, Uttaranchal Institute of Technology, Uttaranchal University, Dehradun-248007, India
  • Arpita Adideo Department of Aerospace Engineering, Uttaranchal Institute of Technology, Uttaranchal University, Dehradun-248007, India
  • Vansh Kumar Department of Aerospace Engineering, Uttaranchal Institute of Technology, Uttaranchal University, Dehradun-248007, India
  • Aditya Rana Uttaranchal UniversityDepartment of Aerospace Engineering, Uttaranchal Institute of Technology, Uttaranchal University, Dehradun-248007, India
  • Abhay Dhasmana Department of Aerospace Engineering, Uttaranchal Institute of Technology, Uttaranchal University, Dehradun-248007, India
  • Shivansh Aggarwal Department of Aerospace Engineering, Uttaranchal Institute of Technology, Uttaranchal University, Dehradun-248007, India
  • Amit Kumar Department of Mechanical Engineering, Uttaranchal Institute of Technology, Uttaranchal University, Dehradun-248007, India

DOI:

https://doi.org/10.37868/dss.v7.id293

Abstract

The traditional black box, or Flight Data Recorder (FDR) and Cockpit Voice Recorder (CVR), has been instrumental in post-crash investigations. Its limitations, such as data loss, difficulty in retrieval from remote or underwater crash sites, and the inability to provide real-time insights, prompted the need for technological advancements. This paper aims to explore the integration of cutting-edge technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), Satellite Communication, GPS, and advanced telemetry systems to revolutionize black box functionality and enhance aviation safety. Next-generation black boxes can leverage real-time encrypted data transmission through satellite connectivity, ensuring immediate access to crucial flight parameters, even before an accident occurs. The incorporation of GPS enables precise aircraft tracking, while telemetry techniques allow monitoring of critical flight parameters, engine health, and environmental conditions. Additionally, the use of underwater acoustic beacons and buoyant ejection modules can expedite black box recovery in case of oceanic crashes, reducing search and rescue operation time. AI-driven predictive analytics further strengthen aircraft monitoring by detecting anomalies and potential system failures, enabling preemptive measures to prevent disasters. The integration of IoT allows seamless connectivity between onboard sensors and ground control stations, ensuring that aviation authorities receive real-time alerts regarding abnormal flight behavior or malfunctions. Moreover, cloud-based data storage ensures redundancy, eliminating the risks of data loss due to hardware damage. By implementing IoT-enabled black boxes, the aviation industry can significantly reduce the risk of flight disappearance, improve accident investigations, and enhance proactive safety measures. The ability to access real-time flight data enhances situational awareness, minimizes investigation delays, and facilitates faster decision-making during in-flight emergencies. This technological evolution in flight data recording and transmission marks a significant step toward a safer, more efficient, and more transparent aviation ecosystem.

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Published

2026-01-24

How to Cite

[1]
S. Srivastava, “Next-Generation Black Box with IOT and Real Time Monitoring ”, Defense and Security Studies, vol. 7, no. 1, pp. 52–59, Jan. 2026.

Issue

Vol. 7 No. 1 (2026)

Section

Articles

License

Copyright (c) 2026 Sachin Srivastava, Arpita Adideo, Vansh Kumar, Aditya Rana, Abhay Dhasmana, Shivansh Aggarwal, Amit Kumar

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