Ecologia Balkanica

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https://doi.uni-plovdiv.bg/handle/store/4
p-ISSN: 1314-0213 / e-ISSN: 1313-9940

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Browsing Ecologia Balkanica by Author "Bekyarova-Tokmakova, Anna"

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    IoT framework for environmental monitoring in Strandzha Nature Park
    (Plovdiv University Press "Paisii Hilendarski", 2025-11-22) Tokmakov, Dimitar; Bekyarova-Tokmakova, Anna; Asenov, Stanislav; Shotarova, Snezha; Lyubomirov, Slavi
    Environmental monitoring plays a critical role in preserving biodiversity and ensuring sustainable management of protected areas. However, traditional monitoring approaches often lack efficiency, precision, and real-time responsiveness. This paper introduces an innovative Internet of Things (IoT) framework specifically designed for environmental monitoring in Strandja Nature Park—a region of significant ecological value located in Bulgaria. The proposed framework integrates advanced sensing technologies, low-power wide-area network (LPWAN) communications (LoRaWAN), and cloud-based analytics to enable real-time tracking of environmental parameters, including air quality, soil moisture, temperature, humidity, and wildlife presence. A practical deployment of the IoT system demonstrates enhanced capabilities in data acquisition, coverage, energy efficiency, and early detection of ecological disturbances. The results highlight significant improvements over conventional methods in terms of accuracy, data granularity, and cost-effectiveness. Ultimately, this framework provides valuable insights for proactive environmental management, paving the way toward a more comprehensive, sustainable, and technologically advanced approach to biodiversity conservation in protected natural regions.
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    IoT sensor node for ammonia monitoring in livestock
    (Plovdiv University Press "Paisii Hilendarski", 2025-11-19) Assenov, Stanislav; Tokmakov, Dimitar; Bekyarova-Tokmakova, Anna; Shotarova, Snezha; Lyubomirov, Slavi
    Increased concentrations of ammonia (NH₃) in livestock buildings pose significant risks to animal welfare, environmental sustainability, and worker safety. The current study presents the design and validation of an Internet of Things (IoT) based sensor node to monitor ammonia concentration (NH₃) in real time in agricultural environments. A microcontroller for local data processing and a wireless communication module that transmits measurements to a cloud platform or mobile application. The prototype has been tested both in controlled laboratory conditions and on real livestock farms, demonstrating high accuracy (±5 ppm), low power consumption (battery power and additional solar panel), and resistance in dusty and humid environments. The collected data is analyzed using machine learning algorithms to predict dangerous levels of NH₃ and automate ventilation controls. The results show that the proposed solution offers a cost-effective and scalable approach to reduce NH₃ emissions, improve animal welfare, and ensure regulatory compliance. Future work includes the integration of additional parameters (e.g., temperature, humidity) and implementation in smart farming systems.