Explore low-cost, energy-efficient sensor data acquisition at scale in this tinyML talk. Delve into the challenges of data scarcity in machine learning projects, particularly for offline businesses requiring smart sensors. Learn about recent advancements in hardware and software optimizations for on-sensor ML model evaluation and training. Discover how Everynet is deploying nationwide telecommunication networks for low-cost, low-power connectivity of battery-powered sensors across multiple countries. Examine implemented use cases and best practices for device-to-cloud energy-aware time series replication. Gain insights into topics such as LoRaWAN ecosystems, network infrastructure, field planning, and the synergy between low-cost connectivity and tinyML. Engage with discussions on physical range, deployment options, power consumption, and scaling strategies for IoT networks.