Rupali P. Shete
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Rupali P. Shete has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Anupkumar M. Bongale
Department of Artificial Intelligence and Machine Learning, Symbiosis Institute of Technology, Pune Campus, Symbiosis International (Deemed University), Pune, India
3 shared publications - Deepak Dharrao
Department of Computer Science and Engineering, Symbiosis Institute of Technology, Pune Campus, Symbiosis International (Deemed University), Pune, India
3 shared publications - Amith Shekhar C.
Department of Computer Science and Engineering, B. N. M. Institute of Technology, Bengaluru, India
1 shared publication - Laxmikantha K1 shared publication
- Shivamurthy Hiremath1 shared publication
- Yogeshwari V. Mahajan
Pimpri Chinchwad College of Engineering & Research, Pune, India
1 shared publication
Latest Publications
- Open Access
- 1 September 2025
- Published by Springer Nature in Discover Internet of Things
- Vol. 5 (1) , 1-31
IoT-driven ensemble machine learning model for accurate dissolved oxygen prediction in aquaculture
- 1 September 2025
- Published by Springer Nature in Discover Internet of Things
- Vol. 5 (1) , 1-31
Open AccessIoT-driven ensemble machine learning model for accurate dissolved oxygen prediction in aquaculture
- Open Access
- 2 August 2025
- Published by Engineering, Technology & Applied Science Research in Engineering, Technology & Applied Science Research
- Vol. 15 (4) , 25133-25139
Lightweight Cryptographic and Scalable IoT Systems for Encryption across GSM-MQTT Architectures in Resource-Constrained Aquaculture Environment
Internet of Things (IoT) technologies in environmental monitoring provide real-time remote data acquisition capabilities and decision-making for different domains, including aquaculture. This study investigates a secure water quality monitoring system designed specifically for fish farms through IoT technology with an emphasis on lightweight encryption methods combined with real-time GSM communications. The primary objective is to protect and maintain the confidentiality, integrity, and operational efficiency of vital pH, Dissolved Oxygen (DO), and Temperature (T) measurements collected by low-power microcontroller devices. A wireless data transmission system was based on Arduino with calibrated analog sensors and the SIM800L GSM module to implement the MQTT protocol for data transfer. The data security assessment involved the implementation and testing of the AES-128-CBC and SPECK-128-CBC symmetric encryption algorithms under equivalent real-time circumstances. SPECK-128-CBC delivered faster encryption (209.64 µs) than AES-128-CBC (235.08 µs) along with improved memory efficiency and more compact payloads, indicating its best fit for constrained environments. AES-128-CBC demonstrated a slightly higher level of ciphertext entropy, reaching 5.18 bits/byte compared to 5.09 of SPECK-128-CBC. Using a weighted scoring method that weighted entropy at 40%, processing speed at 30%, and memory and payload efficiency at 30%, SPECK achieved 0.9931 while AES reached 0.9484. These results suggest that SPECK-128-CBC offers an energy-efficient encryption solution to provide optimal security for GSM-based IoT systems in aquaculture environments.
- 2 August 2025
- Published by Engineering, Technology & Applied Science Research in Engineering, Technology & Applied Science Research
- Vol. 15 (4) , 25133-25139
Open AccessLightweight Cryptographic and Scalable IoT Systems for Encryption across GSM-MQTT Architectures in Resource-Constrained Aquaculture Environment
Internet of Things (IoT) technologies in environmental monitoring provide real-time remote data acquisition capabilities and decision-making for different domains, including aquaculture. This study investigates a secure water quality monitoring system designed specifically for fish farms through IoT technology with an emphasis on lightweight encryption methods combined with real-time GSM communications. The primary objective is to protect and maintain the confidentiality, integrity, and operational efficiency of vital pH, Dissolved Oxygen (DO), and Temperature (T) measurements collected by low-power microcontroller devices. A wireless data transmission system was based on Arduino with calibrated analog sensors and the SIM800L GSM module to implement the MQTT protocol for data transfer. The data security assessment involved the implementation and testing of the AES-128-CBC and SPECK-128-CBC symmetric encryption algorithms under equivalent real-time circumstances. SPECK-128-CBC delivered faster encryption (209.64 µs) than AES-128-CBC (235.08 µs) along with improved memory efficiency and more compact payloads, indicating its best fit for constrained environments. AES-128-CBC demonstrated a slightly higher level of ciphertext entropy, reaching 5.18 bits/byte compared to 5.09 of SPECK-128-CBC. Using a weighted scoring method that weighted entropy at 40%, processing speed at 30%, and memory and payload efficiency at 30%, SPECK achieved 0.9931 while AES reached 0.9484. These results suggest that SPECK-128-CBC offers an energy-efficient encryption solution to provide optimal security for GSM-based IoT systems in aquaculture environments.