An egg flat identification system for identifying an egg flat among a collection of egg flats is provided. Such a system includes a first measurement device configured to determine a first measurement of a plurality of eggs carried by an egg flat. A processor is in communication with the first measurement device. The processor is configured to receive the first measurements from the first measurement device. A second measurement device is configured to determine a second measurement of the eggs in the collection of egg flats. The second measurement device is in communication with the processor such that the processor is capable of receiving the second measurements. The processor compares the second measurements with the first measurements so as to identify a respective egg flat among the collection of egg flats.

A method and an arrangement is provided for determining the location and/or speed of an object configured to move along a controlled trajectory, in connection with which object is fitted a measuring device measuring at least the magnetic field acting on the object in its different locations, which measuring device comprises a device configured to measure the magnetic field, from the measuring data received from which device a magnetic footprint describing the magnetic field acting on the object in its different locations is formed, which magnetic footprint is recorded in connection with a teaching run, or with self-learning, for later use. The location of the object after a teaching run is determined by measuring in essentially real-time in the direction of the three coordinates X, Y, Z of the magnetic field acting on the object moving along a controlled trajectory and by comparing the measurement results to a magnetic footprint recorded in advance and also by deducing as a result of the comparison the exact location of the object on its path of travel.

An electronic device described herein includes a sensing unit having at least one sensor to acquire sensing data. An associated computing device extracts sensor specific features from the sensing data, and generates a motion activity vector, a voice activity vector, and a spatial environment vector as a function of the sensor specific features. The motion activity vector, voice activity vector, and spatial environment vector are processed to determine a base level context of the electronic device relative to its surroundings, with the base level context having aspects each based on the motion activity vector, voice activity vector, and spatial environment vector. Meta level context of the electronic device relative to its surroundings is determined as a function of the base level context, with the meta level context being at least one inference made from at least two aspects of the plurality of aspects of the base level context.