Microgrid-Integrated IoT Systems Enabling Zero-Waste Ecotourism Operations with Predictive Resource Balancing for Climate Resilience

Ecotourism faces mounting pressures from climate change, resource scarcity, and waste proliferation, necessitating innovative solutions for sustainable operations in remote ecosystems. This paper presents a microgrid-integrated Internet of Things (IoT) system that enables zero-waste ecotourism through predictive resource balancing, enhancing climate resilience. The architecture fuses renewable microgrids comprising solar photovoltaics, wind turbines, and biomass digesters with dense IoT sensor networks employing LoRaWAN for real-time monitoring of energy consumption, waste generation, visitor dynamics, and environmental variables. Advanced machine learning algorithms, including long short-term memory (LSTM) networks and mixed-integer linear programming optimizers, forecast demands and dynamically allocate resources, diverting organic waste into biogas for on-site power while recycling inorganics via AI-driven sorting. Pilot deployments in tropical zones demonstrate 35% energy cost reductions, 98% waste diversion rates, and 80% improved uptime during extreme weather simulations. By embedding edge computing and blockchain for secure data integrity, the system scales to federated virtual power plants, offering a blueprint for resilient, circular ecotourism models aligned with UN SDGs. Challenges like cybersecurity and interoperability are addressed, paving pathways for global adoption in biodiversity hotspots.