Patent classifications
G16Y10/05
Smart farming
A method for managing an irrigation system by generating a multi-dimensional model of an environment of the irrigation system; determining irrigation system control options based on the model, a current state of the irrigation system and the environment of the irrigation system; analyzing water spray pattern, wind speed and weather parameters, and beamforming water spray to reach edges of the spray pattern to water a predetermined area; with a drone, inspecting plants or crops for a problem; and controlling the irrigation system to respond to the problem.
Smart farming
A method for managing an irrigation system by generating a multi-dimensional model of an environment of the irrigation system; determining irrigation system control options based on the model, a current state of the irrigation system and the environment of the irrigation system; analyzing water spray pattern, wind speed and weather parameters, and beamforming water spray to reach edges of the spray pattern to water a predetermined area; with a drone, inspecting plants or crops for a problem; and controlling the irrigation system to respond to the problem.
Detecting and preventing network slice failure for 5G or other next generation network
Network slicing can provide logical network partitioning. This introduces a high degree of flexibility to support devices with different requirements in terms of quality of service, as well as to optimize the network usage. However, each one of these networks can be used for distinct business purposes. Thus, individual slice surveillance statistics, including failure messages, can be utilized to alert other slices that share the same infrastructure. Thus, an early recovery action can be prompted based on a single slice's anomalies being shared with other slices.
Detecting and preventing network slice failure for 5G or other next generation network
Network slicing can provide logical network partitioning. This introduces a high degree of flexibility to support devices with different requirements in terms of quality of service, as well as to optimize the network usage. However, each one of these networks can be used for distinct business purposes. Thus, individual slice surveillance statistics, including failure messages, can be utilized to alert other slices that share the same infrastructure. Thus, an early recovery action can be prompted based on a single slice's anomalies being shared with other slices.
ENVIRONMENTAL MATCHING TECHNIQUES
A method includes receiving raw machine data; determining topographic attributes and underlying environmental characteristics; encoding the respective topographic attributes and the underlying environmental characteristics in hexagrid data structures; and storing the hexagrid data structures in a memory. A computing system includes a processor; and a memory storing instructions that, when executed by the one or more processors, cause the computing system to: receive raw machine data; determine topographic attributes and underlying environmental characteristics; encode the respective topographic attributes and the underlying environmental characteristics in hexagrid data structures; and store the hexagrid data structures in the memory. A non-transitory computer readable medium containing program instructions that when executed, cause a computer to: receive raw machine data; determine topographic attributes and underlying environmental characteristics; encode the respective topographic attributes and the underlying environmental characteristics in hexagrid data structures; and store the hexagrid data structures in a memory.
ENVIRONMENTAL MATCHING TECHNIQUES
A method includes receiving raw machine data; determining topographic attributes and underlying environmental characteristics; encoding the respective topographic attributes and the underlying environmental characteristics in hexagrid data structures; and storing the hexagrid data structures in a memory. A computing system includes a processor; and a memory storing instructions that, when executed by the one or more processors, cause the computing system to: receive raw machine data; determine topographic attributes and underlying environmental characteristics; encode the respective topographic attributes and the underlying environmental characteristics in hexagrid data structures; and store the hexagrid data structures in the memory. A non-transitory computer readable medium containing program instructions that when executed, cause a computer to: receive raw machine data; determine topographic attributes and underlying environmental characteristics; encode the respective topographic attributes and the underlying environmental characteristics in hexagrid data structures; and store the hexagrid data structures in a memory.
Method and system for storing emission rights for point and nonpoint source pollution based on internet of things
A method for storing emission rights for point and nonpoint source pollution based on internet of things is provided. In the method, agricultural nonpoint source pollution is monitored based on internet of things; monitoring data of the agricultural nonpoint source pollution is collected and processed; data on migration of the agricultural nonpoint source pollution is analyzed, and an emission reduction amount of storable nonpoint source pollution of the agricultural nonpoint source pollution is calculated; and the emission reduction amount of storable nonpoint source pollution is added to a regional emission rights storage system as reserve emission rights. In this way, the emission reduction amount of nonpoint source pollution can be allocated to industrial point source pollution, and it is possible to combine agricultural nonpoint source pollution emission reductions and industrial point source pollution emissions, to achieve free distribution therebetween.
Method and system for storing emission rights for point and nonpoint source pollution based on internet of things
A method for storing emission rights for point and nonpoint source pollution based on internet of things is provided. In the method, agricultural nonpoint source pollution is monitored based on internet of things; monitoring data of the agricultural nonpoint source pollution is collected and processed; data on migration of the agricultural nonpoint source pollution is analyzed, and an emission reduction amount of storable nonpoint source pollution of the agricultural nonpoint source pollution is calculated; and the emission reduction amount of storable nonpoint source pollution is added to a regional emission rights storage system as reserve emission rights. In this way, the emission reduction amount of nonpoint source pollution can be allocated to industrial point source pollution, and it is possible to combine agricultural nonpoint source pollution emission reductions and industrial point source pollution emissions, to achieve free distribution therebetween.
PREVENTATIVE FAILURE FOR AGRICULTURAL APPLICATIONS
A sensor system is described. The sensor system includes one or more sensor nodes. The sensor nodes are communicatively coupled to a server by way of a network. The sensor nodes may be communicatively coupled to the network by a cellular connection or a LoRa connection to a gateway. The sensor node may measure a variety of information associated with a transport environment, a confined animal feeding environment, or another agricultural environment.
DETECTING AND PREVENTING NETWORK SLICE FAILURE FOR 5G OR OTHER NEXT GENERATION NETWORK
Network slicing can provide logical network partitioning. This introduces a high degree of flexibility to support devices with different requirements in terms of quality of service, as well as to optimize the network usage. However, each one of these networks can be used for distinct business purposes. Thus, individual slice surveillance statistics, including failure messages, can be utilized to alert other slices that share the same infrastructure. Thus, an early recovery action can be prompted based on a single slice's anomalies being shared with other slices.