Browsing by Author "Adhikari, A. M. N. D. S."

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Autonomous quadcopter-based intelligent irrigation system for enhancing crop care
(Faculty of Science, University of Kelaniya Sri Lanka, 2024) Vimansa, W. A. H.; Adhikari, A. M. N. D. S.; Rathnayaka, R. M. P. B.; Dilshan, P. K. S. I.; Attanayake, A. M. V. A.; Randeniarachchi, R. A. N. D.; Hemal, S. B. N. H.; Piyumal, P. L. A. K.; Kumarage, W. G. C.
Efficient crop care and high productivity are paramount to meeting global food demands amid a growing population. Leveraging advanced technologies, including precise irrigation systems conserve vital resources such as water, minimize waste, and foster sustainability. Consequently, the study presented focused on developing an intelligent irrigation system with the facility of real-time environmental monitoring to optimize water usage and increase efficiency through precise, data-driven irrigation practices. The methodology involves an autonomous quadcopter (DJI Tello) hovering over a selected land area and a weather station on the ground. The weather station was created using an ESP32 microprocessor equipped with several sensors; a DHT11 sensor, Infrared counting sensor module, Capacitive soil moisture sensor (MD0247), water level sensor (MD0207), and LDR sensor (MD0222) to monitor temperature, humidity, rainfall, wind speed, solar intensity, and soil moisture. Furthermore, a computer vision model was developed using YOLOV8 to identify the selected three crops: Arachis hypogaea, Capsicum annuum, and Antherella Sessilis. The developed irrigation system demonstrated outstanding water delivery performance by effectively reducing wastage of water by 20% and enhancing crop growth rates by 10%. This enhancement is ascribed to real-time environmental monitoring and continuous analysis of data from the sensors of the weather station. Moreover, the acquired data is stored in a database and displayed through a user-friendly web application where the data is precisely analyzed and displayed as a dashboard. Web application is aimed at user convenience providing users with location-based weather forecasts, sensor outputs and user tips while predicting the amount of water needed to be delivered in upcoming months. The findings in the presenting work highlighted significant improvements in both irrigation efficiency and crop yield. This demonstrates its potential to be applied in agriculture more extensively by adapting to different environmental conditions and crop needs. Furthermore, the developed web application integrates real-time monitoring and computer vision, providing actionable insights that democratize agricultural knowledge and improve agricultural outcomes. In conclusion, the findings signify a significant leap forward in agricultural technology, addressing inherent challenges of traditional farming with sustainable solutions. This initiative not only aims to enhance agricultural productivity but also aligns with broader goals of promoting sustainable and environmentally friendly farming practices.
A cost-effective and adaptable queue management system to increase efficiency in patient queue management
(Faculty of Science, University of Kelaniya Sri Lanka, 2024) Adhikari, A. M. N. D. S.; Gunarathna, T. G. L.; Bandara, K. D. Y.; Gunawardana, K. D. B. H.; Seneviratne, J. A.; Perera, M. H. M. T. S.
Healthcare systems worldwide, particularly in resource-limited settings like Sri Lanka, face significant challenges related to high patient volumes and constrained resources. These challenges often lead to extended wait times and reduced patient satisfaction. This study presents an innovative, adaptable queue management system designed to replace inefficient manual methods, enhance operational efficiency, and optimise patient flow. Scalable to meet the needs of both small clinics and large hospitals, the system functions across various connectivity scenarios, ensuring flexibility in diverse environments. The system comprises patient, doctor, and administrative interfaces. Upon patient registration, a QR code will be generated, and the patient can use the QR code to check-in. A printed queue token will be issued when a patient checks-in. Doctors can manage their queues and access real-time patient information. Administrators oversee overall system operations, including advertisement management and key performance indicator (KPI) tracking, to monitor and enhance healthcare delivery in addition to having the ability to add, remove, or edit users. Built on a robust technology stack that includes HTML, CSS, JavaScript, PHP, SQLite3 for database management, and AES-256-CBC encryption for secure data handling, the system is designed for reliability and scalability. Embedded ESP32 devices with OLED displays and LEDs provide offline functionality, while multicast DNS (mDNS) ensures seamless device connectivity to local networks without requiring Internet access which is critical for rural healthcare facilities. The system features a custom-built algorithm, leveraging Random Forest Regression, to analyse historical and real-time queue data. This allows for precise queue time estimates and significantly improves staff and patient planning. The system outperforms the traditional manual systems, which lack both real-time prediction capabilities and efficiency. The system performance was meticulously improved using various optimisation techniques such as batch processing, database indexing, and algorithm optimisation, which led to an execution time of 22 seconds to be brought down to 1.5 seconds on a 1.4 million row data set, where the execution involved processing, sorting, encrypting, decrypting, and storing data. A one-tailed t-test was performed to compare the execution times of test runs with optimisation and without optimisation. There was a significant difference in execution times between test runs without optimization (M = 21.84, SD = 1.16) and execution times between test runs with optimization (M = 1.52, SD = 0.28); t(43) = 107.76, p < 0.001. The system was validated for 10 years of sample data and the results demonstrate that the system is robust and responsive under real-world conditions. Continuous validation is ongoing in diverse healthcare environments to further assess its impact on optimizing queue management, resource allocation, and patient satisfaction. This scalable and adaptable system represents a substantial advancement in healthcare management, offering a transformative solution to meet the evolving needs of healthcare facilities despite scarce infrastructure.
Wireless pager system for enhancing emergency communication in hospital environment
(Faculty of Science, University of Kelaniya Sri Lanka, 2024) Gunarathna, T. G. L.; Adhikari, A. M. N. D. S.; Bandara, K. D. Y.; Gunawardana, K. D. B. H.; Seneviratne, J. A.; Perera, M. H. M. T. S.
Maintaining fast and efficient communication between hospital staff is critical to ensure patient safety during emergencies. However, challenges such as the lack of Global System for Mobile Communications (GSM) signals in countries like Sri Lanka and the risk of using cable communication during hazardous weather conditions further complicate emergency communication. This paper proposes a wireless pager system utilizing LoRa (Long Range) technology to facilitate seamless interaction between doctors, nurses, and other supportive and administrative staff in a hospital. LoRa operates on sub-gigahertz frequencies, providing robust signal penetration and extended range, making it ideal for hospital environments where walls and infrastructure often disrupt traditional signals. The proposed system consists of three primary modules: the Ward Module, Central Hub, and Doctor Module. The Ward Module, placed in hospital wards, allows nurses to trigger emergency alerts by selecting an available doctor. It also provides status updates on message delivery and doctors' responses. The Central Hub acts as the system's control center, maintaining a database of doctors and wards, managing doctor availability, registering new entries, and logging communication transactions. It utilizes a web-based application to handle and collect data, which runs on the Central Hub, streamlining data management and access. The Hub also backs up data to the cloud and stores it locally during internet outages, synchronizing once the connection is restored. The Doctor Modules enable doctors to log their presence by selecting their ID from a list obtained from the Central Hub. This login data is updated in the Central Hub and shared with the Ward Modules. Upon receiving an emergency alert, doctors can respond by accepting, canceling, or forwarding the message, with the updated status being communicated back to the Ward Module. The system was tested in a simulated hospital environment using two Ward Modules, two Doctor Modules, and a Central Hub, covering a 200m distance. Both the Ward and Doctor Modules were built using ESP32 microcontrollers with LoRa modules operating at 433 MHz, while the Central Hub was developed using a Raspberry Pi single board computer with a LoRa module. The system demonstrated reliable performance, maintaining stable communication across the test range. It also demonstrated potential for larger hospitals, with extended range possible through proper antenna configuration. A 96% success rate was recorded, with message transmission in under 2 seconds. While LoRa offers robust long-range communication with low power use, its limited bandwidth poses challenges for large data transmission. However, for emergency pager systems, the trade-off between power efficiency and data capacity is acceptable. The system operates independently of traditional communication infrastructure, providing hospitals with a sustainable and resilient solution for emergency communication. It streamlines emergency response in hospital wards by enabling realtime communication and status updates between staff, ensuring fast and accurate transmission of critical information. This enhances the efficiency of interventions and improves patient care outcomes.