Event Filtering Profile for IoT Sensor Data
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Solution Overview
Problem
In the era of IoT, recurring events continue to be transmitted and processed unnecessarily, leading to significant computational and power resource utilization, as there is no effective means to prevent such events from being sent to event processing devices once they are no longer necessary.
Innovation Solution
A method that detects recurring events and uses a user profile with conditions to determine whether to transmit them to an event processing device, reducing unnecessary transmissions and conserving resources by analyzing the profile for frequency, location, and velocity-based criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If recurring events are continuously transmitted to the event processing device, then complete event monitoring is maintained, but network bandwidth and computational resources are excessively consumed
Solution Approach 1:
The system performs preliminary actions by establishing event filtering rules and subscription criteria before recurring events occur. The event processing device pre-configures which event types, sources, and conditions should trigger transmissions, allowing the system to proactively filter events before they are transmitted, thus avoiding unnecessary network and computational resource consumption while maintaining monitoring completeness.
Solution Approach 2:
The invention extracts and removes unnecessary recurring events from the transmission stream by implementing filters that identify and exclude events matching predefined exclusion criteria. This extraction process separates essential events that require processing from redundant events that can be discarded, reducing network bandwidth consumption and computational load on both the event emitting and processing devices.
2Loss of information
If all recurring events are transmitted and processed, then no event information is lost, but power consumption on emitting and processing devices increases significantly
Solution Approach 1:
The event emitting device performs self-service by locally evaluating events against subscription criteria and filtering rules before transmission. This self-filtering capability allows the device to autonomously determine which events warrant transmission based on their own stored configuration, reducing the computational burden on remote processing devices and minimizing power consumption on both ends while ensuring no relevant information is lost.
Solution Approach 2:
Power consumption is reduced through preliminary configuration of event filtering criteria stored locally on the emitting device. By pre-establishing which event types and conditions should be transmitted, the system avoids the energy-intensive process of transmitting and processing all recurring events, while still maintaining complete information about events that meet the subscription criteria.
3Loss of energy
If recurring events are filtered using a profile with conditions, then unnecessary transmissions are prevented, but device complexity increases
Solution Approach 1:
The filtering profile extracts only the essential criteria needed for event evaluation, separating necessary condition checks from unnecessary processing. By defining specific event types, sources, and conditions that trigger transmissions, the system removes complexity by focusing only on relevant evaluation parameters rather than analyzing all possible event attributes, thus reducing device complexity while preventing unnecessary transmissions.
4Loss of energy
If event filtering is implemented on the event emitting device, then network bandwidth is reduced, but computation resources on the emitting device increase
Solution Approach 1:
The emitting device performs self-service filtering by maintaining local copies of subscription criteria and independently evaluating events against these criteria. This approach distributes the filtering computation to the source device, reducing network bandwidth utilization by preventing unnecessary transmissions before they occur, while the self-service nature minimizes the overall system computational burden.
Data Source
AI summary
A method, system and computer program product for efficiently utilizing resources in processing recurring events. Recurring events from one or more event type sources (heart rate monitor) sensed by various sensors are detected. An event type (e.g., heart rate data) for each detected recurring event is identified. A user profile associated with the identified event type is then analyzed to determine whether the associated sensed recurring event is to be transmitted to the event processing device. The user profile contains a set of conditions which need to be satisfied before the recurring event is transmitted to the event processing device. If the set of conditions in the user profile is not satisfied, then the recurring event is not transmitted to the event processing device. In this manner, by not transmitting the recurring event, power and consumption utilization are reduced for both the event emitting device and the event processing device.