Integrated Communication Sensing for IoT Sensor Data Saturation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The proliferation of IoT sensors generates overwhelming amounts of data, leading to network congestion, power inefficiencies, and financial burdens, necessitating a solution to manage sensor saturation and optimize sensor operations.
Innovation Solution
A sensing service provider platform that aggregates sensor data, applies filters for quality and relevance, and adjusts sensor operations based on analytics to identify the most useful sensors, enabling self-differentiation and self-healing capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of IoT sensors is increased to enhance monitoring capabilities, then measurement precision and coverage are improved, but network congestion and data overload occur
Solution Approach 1:
The patent extracts and removes redundant or low-quality sensor data from the network stream through filtering mechanisms. The system identifies and eliminates duplicate measurements, irrelevant data, and low-confidence readings, thereby reducing overall data volume while preserving essential monitoring capabilities.
Solution Approach 2:
The patent segments sensor data into different quality tiers and prioritizes transmission based on importance. High-quality, critical sensor data is transmitted with higher priority, while lower-quality or less critical data is either aggregated, compressed, or transmitted with lower priority, reducing network congestion.
2Reliability
If all sensors operate continuously to ensure data availability, then reliability is improved, but energy consumption increases
Solution Approach 1:
The patent implements dynamic sensor operation modes where sensors can switch between active, standby, and sleep states based on real-time quality assessments and environmental conditions. Sensors that demonstrate consistent high-quality readings may operate in lower-power modes, while those showing degradation are activated more frequently for calibration or replacement.
Solution Approach 2:
The system continuously monitors sensor performance metrics and uses this feedback to adjust operational parameters. When sensor quality deteriorates, the system triggers recalibration, replacement, or increased sampling frequency, ensuring data reliability while minimizing unnecessary energy consumption from continuously operating degraded sensors.
3Productivity
If sensor data is processed in real-time to provide immediate insights, then productivity is improved, but computational complexity and resource requirements increase
Solution Approach 1:
The patent performs preliminary filtering, validation, and quality assessment of sensor data at the edge devices or gateways before data enters the main processing system. This preliminary action reduces the volume and complexity of data requiring advanced processing, enabling real-time insights with reduced computational burden on centralized systems.
Data Source
AI summary
Aspects of the subject disclosure may include, for example, determining, based on an identified context, that there is a need for sensor-related operations, mapping the need to one or more sensors, receiving, from the one or more sensors, data associated with the sensor-related operations, resulting in received data, performing analytics on the received data by applying one or more filters thereto, and causing operational adjustments to be made to the one or more sensors based on the analytics. Other embodiments are disclosed.