Ali Eghmazi

Dr. Ali Eghmazi


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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10 January 2024 in IoT
Verified
Journal Article
Open access
PDF file
AEAli Eghmazi
Ali Eghmazi
MAMohammadhossein Ataei
Mohammadhossein Ataei
RLRene Jr Landry
Rene Jr Landry
GCGuy Chevrette
Guy Chevrette
The Internet of Things (IoT) is a technology that can connect billions of devices or “things” to other devices (machine to machine) or even to people via an existing infrastructure. IoT applications in real-world scenarios include smart cities, smart houses, connected appliances, shipping, monitoring, smart supply chain management, and smart grids. As the number of devices all over the world is increasing (in all aspects of daily life), huge amounts of data are being produced as a result. New issues are therefore arising from the use and development of current technologies, regarding new applications, regulation, cloud computing, security, and privacy. The blockchain has shown promise in terms of securing and preserving the privacy of users and data, in a decentralized manner. In particular, Hyperledger Fabric v2.x is a new generation of blockchain that is open source and offers versatility, modularity, and performance. In this paper, a blockchain as a service (BaaS) application based on Hyperledger Fabric is presented to address the security and privacy challenges associated with the IoT. A new architecture is introduced to enable this integration, and is developed and deployed, and its performance is analyzed in real-world scenarios. We also propose a new data structure with encryption based on public and private keys for enhanced security and privacy.

14 July 2023 in Sensors
Verified
Journal Article
Open access
PDF file
ALI SHAKERIANALI SHAKERIAN
ALI SHAKERIAN
AEAli Eghmazi
Ali Eghmazi
JGJustin Goasdoué
Justin Goasdoué
RLRene Jr Landry
Rene Jr Landry
This paper proposes a novel Blockchain-based indoor navigation system that combines a foot-mounted dual-inertial measurement unit (IMU) setup and a zero-velocity update (ZUPT) algorithm for secure and accurate indoor navigation in GNSS-denied environments. The system estimates the user’s position and orientation by fusing the data from two IMUs using an extended Kalman filter (EKF). The ZUPT algorithm is employed to detect and correct the error introduced by sensor drift during zero-velocity intervals, thus enhancing the accuracy of the position estimate. The proposed Low SWaP-C blockchain-based decentralized architecture ensures the security and trustworthiness of the system by providing an immutable and distributed ledger to store and verify the sensor data and navigation solutions. The proposed system is suitable for various indoor navigation applications, including autonomous vehicles, robots, and human tracking. The experimental results provide clear and compelling evidence of the effectiveness of the proposed system in ensuring the integrity, privacy, and security of navigation data through the utilization of blockchain technology. The system exhibits an impressive ability to process more than 680 transactions per second within the Hyperledger-Fabric framework. Furthermore, it demonstrates exceptional accuracy and robustness, with a mean RMSE error of 1.2 m and a peak RMSE of 3.2 during a 20 min test. By eliminating the reliance on external signals or infrastructure, the system offers an innovative, practical, and secure solution for indoor navigation in environments where GNSS signals are unavailable.

8 December 2023 in Sensors
Verified
Journal Article
Open access
PDF file
MAMohammadhossein Ataei
Mohammadhossein Ataei
AEAli Eghmazi
Ali Eghmazi
ALI SHAKERIANALI SHAKERIAN
ALI SHAKERIAN
RLRene Jr Landry
Rene Jr Landry
GCGuy Chevrette
Guy Chevrette
In the Internet of Things (IoT) era, the surge in Machine-Type Devices (MTDs) has introduced Massive IoT (MIoT), opening new horizons in the world of connected devices. However, such proliferation presents challenges, especially in storing and analyzing massive, heterogeneous data streams in real time. In order to manage Massive IoT data streams, we utilize analytical database software such as Apache Druid version 28.0.0 that excels in real-time data processing. Our approach relies on a publish/subscribe mechanism, where device-generated data are relayed to a dedicated broker, effectively functioning as a separate server. This broker enables any application to subscribe to the dataset, promoting a dynamic and responsive data ecosystem. At the core of our data transmission infrastructure lies Apache Kafka version 3.6.1, renowned for its exceptional data flow management performance. Kafka efficiently bridges the gap between MIoT sensors and brokers, enabling parallel clusters of brokers that lead to more scalability. In our pursuit of uninterrupted connectivity, we incorporate a fail-safe mechanism with two Software-Defined Radios (SDR) called Nutaq PicoLTE Release 1.5 within our model. This strategic redundancy enhances data transmission availability, safeguarding against connectivity disruptions. Furthermore, to enhance the data repository security, we utilize blockchain technology, specifically Hyperledger Fabric, known for its high-performance attributes, ensuring data integrity, immutability, and security. Our latency results demonstrate that our platform effectively reduces latency for 100,000 devices, qualifying as an MIoT, to less than 25 milliseconds. Furthermore, our findings on blockchain performance underscore our model as a secure platform, achieving over 800 Transactions Per Second in a dataset comprising 14,000 transactions, thereby demonstrating its high efficiency.