A review of 28 studies reports that agricultural TinyML deployments largely rely on ESP32, STM32, and ATMega microcontrollers. Some plant-disease detection systems report 90–97% accuracy and latency as low as 7.6 ms, but memory and energy metrics are often missing. The review says models typically run inference on-device in the field while training remains in the cloud. Quantization appears in over half of deployments, whereas structured pruning and neural architecture search are rare.
Ai2 released OlmoEarth v1.3 with global satellite embeddings and a browser-based explorer. The tools support exploring change over time and finding similar places in satellite data.
Google DeepMind and partners released a map distinguishing forest and land-use types. Forest Typology 2020 categorizes ten-metre land patches, helping distinguish natural forests, plantations and agricultural land.
