International business machines corporation (20240179062). CREATING SETS OF HETEROGENEOUS INTERNET-OF-THINGS (IoT) DEVICES FROM WHICH TO UPLOAD DATA AS A PRE-STEP TO EDGE COMPUTING simplified abstract
Contents
- 1 CREATING SETS OF HETEROGENEOUS INTERNET-OF-THINGS (IoT) DEVICES FROM WHICH TO UPLOAD DATA AS A PRE-STEP TO EDGE COMPUTING
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 CREATING SETS OF HETEROGENEOUS INTERNET-OF-THINGS (IoT) DEVICES FROM WHICH TO UPLOAD DATA AS A PRE-STEP TO EDGE COMPUTING - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
CREATING SETS OF HETEROGENEOUS INTERNET-OF-THINGS (IoT) DEVICES FROM WHICH TO UPLOAD DATA AS A PRE-STEP TO EDGE COMPUTING
Organization Name
international business machines corporation
Inventor(s)
Hemant Kumar Sivaswamy of Pune (IN)
Venkata Vara Prasad Karri of Visakhapatnam (IN)
Sarbajit K. Rakshit of Kolkata (IN)
Afroz Khan I of Davanagere (IN)
CREATING SETS OF HETEROGENEOUS INTERNET-OF-THINGS (IoT) DEVICES FROM WHICH TO UPLOAD DATA AS A PRE-STEP TO EDGE COMPUTING - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240179062 titled 'CREATING SETS OF HETEROGENEOUS INTERNET-OF-THINGS (IoT) DEVICES FROM WHICH TO UPLOAD DATA AS A PRE-STEP TO EDGE COMPUTING
Simplified Explanation
The abstract describes a method for transmitting data from a set of edge devices, including identifying IoT devices, grouping them, deploying ML models on primary devices, and activating other groups in response to events.
- Identifying IoT devices within a structure
- Grouping IoT devices into groups
- Selecting primary devices for each group
- Deploying ML models on primary devices
- Activating other groups based on events
Potential Applications
This technology could be applied in smart home systems, industrial automation, and environmental monitoring.
Problems Solved
This technology helps in efficient data transmission, event detection, and resource optimization in IoT networks.
Benefits
The benefits of this technology include improved data processing, faster response to events, and enhanced network efficiency.
Potential Commercial Applications
The potential commercial applications of this technology could be in smart home devices, industrial IoT solutions, and smart city infrastructure.
Possible Prior Art
One possible prior art could be the use of centralized servers for data processing in IoT networks. However, the deployment of ML models on edge devices for event detection and group activation is a novel approach.
What is the impact of deploying ML models on primary devices in IoT networks?
Deploying ML models on primary devices in IoT networks allows for real-time event detection and decision-making at the edge, reducing latency and improving network efficiency.
How does grouping IoT devices help in resource optimization?
Grouping IoT devices helps in distributing tasks efficiently, reducing redundant data transmission, and optimizing resource usage within the network.
Original Abstract Submitted
according to one embodiment, a method, computer system, and computer program product for transmitting data from a set of edge devices is provided. the embodiment may include identifying one or more internet-of-things (iot) devices within a structure. the embodiment may include combining the identified one or more iot devices into one or more groups. the embodiment may include identifying a respective primary device for each group of the one or more groups. the embodiment may include deploying a tiny machine learning (ml) model on each identified respective primary device. in response to detection of an event within the structure by a group of the one or more groups, the embodiment may include utilizing the tiny ml model of a primary device of the group to select one or more other groups for activation.
