De Martinis M, et al. World J Mens Health. 2020 Jan;38:e62. https://doi.org/10.5534/wjmh.200099

In the contemporary era, the global proliferation of Internet of Things (IoT) devices exceeds 15 billion, serving functions from wearables to smart grid monitoring. These devices frequently manage sensitive data, underscoring the need for secure and reliable IoT networks leveraging blockchain technology. A key innovation of this study is an approach to mitigate vulnerabilities that quantum computing poses to blockchain-based IoT systems, which existing cryptographic methods cannot effectively address. Quantum computers could exploit these weaknesses to compromise key-pair generation and extract private keys from transaction signatures. To overcome this, the research introduces an optimized implementation of the post-quantum digital signature algorithm Dilithium-5, ensuring blockchain security and quantum readiness. These transaction signatures are designed for low-power, cost-effective microcontrollers, such as the ESP32, making the solution accessible for a wide range of IoT devices. In addition, the study includes a case study involving a post-quantum safe portable device for measuring blood oxygen levels and heart rate, illustrating the practical benefits and effectiveness of the proposed solution in enhancing IoT security against quantum threats. The results demonstrate that the proposed approach ensures quantum-resistant security while maintaining performance efficiency, making it suitable for real-world IoT applications.

Hand tracking and gesture recognition are fundamental in a multitude of applications. Various sensors have been used for this purpose, however, all monocular vision systems face limitations caused by occlusions. Wearable equipment overcome said limitations, although deemed impractical in some cases. Using more than one sensor provides a way to overcome this problem, but necessitates more complicated designs. In this work, we aim to highlight contemporary methods used for hand tracking and gesture recognition by collecting publications of systems developed in the last decade, that employ contactless devices as RGB cameras, IR, and depth sensors, along with some preceding pillar works. Additionally, we briefly present common steps, techniques, and basic algorithms used during the process of developing modern hand tracking and gesture recognition systems and, finally, we derive the trend for the next future.