August 2022
Faculty and students presented the following papers virtually at IEEE 9th International Conference on Future Internet of Things and Cloud (FiCloud 2022), Rome, Italy from 22 – 24 August:
- Improving IoT-based smart retrofit model for analog water meters using DL based algorithm: Ayush Kumar Lall, Dual Degree 4th year (ECD); Dr. Sachin Chaudhari; Ansh Khandelwal, B.Tech 4th year (ECE) and Nitin Nilesh- M.S Final year (CSE).
Research work as explained by the authors: This paper proposes a DL-based algorithm which is used for improving the performance of digit detection from IoT-based analog water meters. The DL algorithm is trained on a rich dataset of over 160,000 images collected from six water nodes deployed at locations with different environmental conditions. A detailed comparison between the proposed DL and ML algorithm is made based on detection accuracy, feature analysis, error analysis, and computational complexity analysis. It is observed that compared to the ML model, the proposed DL model maintained a higher detection accuracy and is more generalized in terms of feature extraction, which makes the algorithm robust.
- CV and IoT-based Remote Triggered Labs: Use Case of Conservation of Mechanical Energy: K S Viswanadh, Dual Degree 4th year (ECD); Nitin Nilesh, Nitin Nilesh- M.S Final year (CSE); Dr. Sachin Chaudhari; Dr. V Choppella; O Kathalkar and P Vinzey, research interns under Dr Sachin from St. Pallotti college, Nagpur.
Research work as explained by the authors: In this paper, the use of Computer-Vision (CV) is demonstrated for Remote Triggered L ab experiments. For this, a use-case of the Conservation of Mechanical Energy experiment is considered. A CV-based approach is used to estimate an object’s velocity whose setup primarily consists of a microprocessor, a camera and infrared (IR) sensors. The experiment is recorded, and various CV techniques are employed to estimate the object’s velocity. This paper also compares a CV-based and a IR sensor-based approach to estimate the object’s velocity. Linear regression applied on the CV-based implementation resulted in an optimal mean-squared error (MSE), nearly 10 times better than IR-based implementation.
The theme of this conference was to promote the state-of-the-art in scientific and practical research of the IoT and cloud computing. It provided a forum for bringing together researchers and practitioners from academia, industry, and public sector in an effort to present their research work and share research and development ideas in the area of IoT and cloud computing.
Conference page: https://www.ficloud.org/2022/index.php