Siemens had ten patents in edge computing during Q3 2023. Siemens AG filed several patents during Q3 2023. One patent is for a method and system to control a sensor system by comparing measured energy consumption profiles with expected profiles and executing control commands based on the closest match. Another patent is for controlling access to computer programs on an embedded system, with different runtime modes and IT-security constraints. A technical injection system patent involves injecting a retrained machine learning model from one computing unit to another at runtime. Lastly, there is a patent for a recommendation system and method to determine the optimal compression rate for an AI model based on runtime properties and desired outcomes. GlobalData’s report on Siemens gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
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Siemens grant share with edge computing as a theme is 0% in Q3 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Controlling a sensor system (Patent ID: US20230266152A1)
Siemens AG has filed a patent for methods and systems to control a sensor system. The patent describes a method where an energy measuring apparatus is used to sense the energy consumption profile of the sensor system. This measured profile is then compared to one or more expected energy consumption profiles. The closest expected energy consumption profile is selected, and based on this selection, control commands are defined. The sensor system is then controlled by executing these control commands.
The patent also includes additional claims. Claim 2 states that the elements of the method can be repeated during the use of the sensor system. Claim 3 introduces the concept of assigning a state to the sensor system and matching the control command to this state. The state can include factors such as the configuration of the sensor system, environmental conditions, modifications, hardware defects, malfunctions, or unauthorized interventions. Claim 4 specifically lists these possible states.
Claim 5 mentions that the expected energy consumption profiles can be produced by a sensor system model. This model can be implemented in a cloud environment, on an edge device, or directly on the sensor system itself. Claim 6 provides this flexibility in implementation.
Claim 7 introduces the concept of assigning uncertainty values and tolerances to the expected energy consumption profiles. These values are used when identifying the closest energy consumption profile. Claim 8 states that an associated deviation can be determined when identifying the closest energy consumption profile.
Claim 9 describes the various control commands that can be included in the method. These commands include energy control, energy optimization, reducing the amount of energy fed in, regulating the energy state of the sensor system, reading warning signals, transmitting error and warning messages, activating another sensor system, and switching off the sensor system.
The patent also includes a system comprising an energy measuring apparatus, a comparison unit, an identification unit, a definition unit, and a control unit. The energy measuring apparatus senses the energy consumption profile of the sensor system, and the comparison unit compares it to expected energy consumption profiles. The identification unit identifies the closest energy consumption profile, and the definition unit defines control commands based on this profile. The control unit then executes these control commands to control the sensor system. The definition unit in this system includes an energy management unit designed to optimize energy consumption by the sensor system.
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