Dataset for worker activity recognition and efficiency estimation during manual harvesting

This dataset contains harvest data collected during manual strawberry harvesting with instrumented picking carts in Santa Maria, CA, USA, in 2024. The data includes geo-tagged harvest mass, cart location, and motion recorded by a GPS receiver, an Inertial Measurement Unit (IMU), and load cells. Each data point is annotated as either "Pick" (indicating active picking) or "NoPick" (indicating no active picking). This dataset can be used to train, validate, and test AI algorithms to recognize worker activity during manual fruit harvesting and quantify worker efficiency. It is valuable for researchers and practitioners in precision agriculture and agricultural automation who are working on optimizing labor and field management, as well as developing strawberry harvesting machines or harvest assist systems.