Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
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This Author published in this journals
All Journal International Journal of Reconfigurable and Embedded Systems (IJRES) International Journal of Informatics and Communication Technology (IJ-ICT)
Akshatha Naik
Moodlakatte Institute of Technology
Computer Science & IT Economics, Econometrics & Finance

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IoT-enabled smart hydroponic system using nutrient film technique for precision agriculture Varuna Kumara; Akshatha Naik; Fatima Tahsir; Sinchana Bommayya Devadiga; Vinitha Ramesh Naik
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v15i2.pp900-908

Abstract

The study aims to develop an internet of things (IoT)-enabled automated hydroponic system using the nutrient film technique (NFT) to optimize plant growth with minimal human intervention. The system integrates sensors, microcontrollers, and cloud-based monitoring to maintain optimal conditions for crops. The system utilizes Arduino Uno, ESP8266 Wi-Fi module, and sensors including pH, TDS, DHT11 and water level sensors. Data collected from these sensors is processed in real time, allowing automated adjustments through relay-controlled water and nutrient pumps. The system transmits data to the ThingSpeak IoT platform, enabling remote monitoring and predictive analytics. The proposed hydroponic system ensures stable environmental conditions, improving plant growth efficiency. Key parameters such as pH, TDS levels and humidity are maintained within optimal ranges. The automated system reduces manual intervention, enhances water and nutrient efficiency, and increases yield consistency compared to traditional farming methods. The IoT-based NFT hydroponic system demonstrates significant potential in urban agriculture and controlled environment farming. By leveraging automation, AI-driven analytics, and cloud-based monitoring, it provides a scalable and sustainable solution for precision farming. Future advancements may include AI-based predictive analytics, solar-powered energy solutions, and robotic automation for further optimization.
An IoT-enabled vision-aid for the blind integrating ultrasonic obstacle detection and GPS-based location tracking Varuna Kumara; Akshatha Naik; Ashwini Ashwini; Navilgone Krishna Vaishnavi; Ruchitha Kamath Subhashchandra; Trapthi Trapthi
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 15, No 2: July 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v15.i2.pp386-395

Abstract

Visual impairment significantly affects independent mobility and personal safety, creating a need for affordable and reliable assistive navigation technologies. This paper presents the design and implementation of a low-cost wearable Vision-Aid system to support visually impaired individuals during outdoor navigation. The primary objective of the study is to enhance obstacle awareness, location tracking, and emergency communication using accessible embedded technologies. The proposed system integrates ultrasonic sensors for real-time obstacle detection, an Arduino microcontroller for data processing, a global positioning system (GPS) module for location tracking, and a global system for mobile communication (GSM) module for emergency alert transmission. Audio feedback is provided through a voice module to guide the user safely. Experimental evaluations were conducted under various environmental conditions to assess obstacle detection accuracy, response time, and location reliability. The results demonstrate accurate obstacle detection, timely audio alerts, and reliable real-time location sharing with caregivers. The proposed system improves user confidence, mobility, and safety while maintaining low implementation cost. This work highlights the potential of embedded and internet of things (IoT)–based assistive devices to enhance autonomy for visually impaired individuals and provides a foundation for future integration of artificial intelligence (AI)-based object recognition.
Co-Authors Ashwini Ashwini Fatima Tahsir Navilgone Krishna Vaishnavi Ruchitha Kamath Subhashchandra Sinchana Bommayya Devadiga Trapthi Trapthi Varuna Kumara Varuna Kumara Vinitha Ramesh Naik