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@article{180613,
        author = {MADREWAR OM JITENDRA and Manav Rajendra Kothari and Muffadal Shabbir Patrawala and Harshada Machindra Pote and Prof. Madhavi Bhosale},
        title = {Tree Health Monitoring and Management System using IoT},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {1758-1762},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180613},
        abstract = {This paper explores innovative approaches to 
environmental and tree health monitoring using IoT, 
machine learning, and advanced communication 
systems. A LoRaWAN-based sensor system for urban 
trees collects real-time data on soil moisture, 
temperature, 
and humidity, improving tree 
management. Another study focuses on an IoT system 
for coconut trees, enhancing remote agricultural 
decision-making. A heterogeneous neural network 
(HNN) predicts the Urban Tree Health Index (UTHI) 
with high accuracy, automating tree assessments. 
Lastly, a hybrid edge computing and LoRa 
architecture enables real-time forest monitoring, 
addressing challenges like deforestation and climate 
change. Together, these technologies promote 
sustainable forestry and tree health management.},
        keywords = {LoRaWAN, HNN, UTHI, edge  computing, remote sensing, ThingSpeak.},
        month = {June},
        }