IoT Sensor Replication for Smart Home Reliability
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Solution Overview
Problem
In IoT settings, particularly in smart homes, there is a challenge in determining the need for sensor replication due to potential malfunctions, which can lead to false or incomplete data, especially for individuals with limited mobility or medical conditions, and it is not cost-effective to replicate sensors in every location.
Innovation Solution
A method and apparatus that utilize a processor to connect with sensors, input rules associating sensors with activities of daily living (ADLs), assign quantitative utility values to ADLs, and identify necessary sensors based on these values to ensure accurate monitoring and minimize costs by determining which sensors to replicate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensors are replicated in every location to ensure reliable monitoring, then monitoring reliability is improved, but deployment and maintenance costs increase
Solution Approach 1:
The patent applies local quality by differentiating sensor replication strategies based on location-specific risk assessments. Instead of uniform replication, the system identifies critical locations where sensor failures would have the greatest impact on ADL monitoring and replicates sensors only at those locations, optimizing the balance between reliability and cost.
Solution Approach 2:
The system performs preliminary analysis by simulating sensor failures before actual deployment to predict which sensors are most critical. This advance preparation allows the system to pre-identify which locations require sensor replication to maintain monitoring reliability under failure conditions.
2Measurement precision
If all sensors are replicated to maintain monitoring accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent implements local quality by applying differential replication strategies to different locations based on their criticality. The system identifies which locations have the highest impact on ADL monitoring accuracy and replicates sensors only there, avoiding unnecessary replication in less critical areas and thus reducing overall system complexity.
Solution Approach 2:
The system applies partial action by replicating sensors only to the extent necessary to maintain monitoring accuracy under failure conditions, rather than replicating all sensors uniformly. This selective approach maintains sufficient measurement precision while avoiding excessive replication that would increase complexity.
3Reliability
If sensor replication is performed without risk assessment, then monitoring reliability is improved, but loss of energy increases
Solution Approach 1:
The patent applies local quality by implementing location-specific replication strategies based on risk assessments. The system identifies critical locations where sensor failures would most severely impact monitoring and replicates sensors only at those locations, thereby minimizing the total number of sensors required and reducing overall energy consumption while maintaining necessary reliability.
Data Source
AI summary
Methods and arrangements identifying sensors deployed in an internet of things to assist in determining a need for sensors. A plurality of sensors are connected with. A set of rules are inputted to at least one processor, wherein the rules associate particular sensors within the plurality of sensors with tasks associated with a plurality of activities of daily living. A quantitative utility value is assigned to each of the activities of daily living within the plurality of activities of daily living. The quantitative utility value of each of the activities of daily living and the tasks associated with the activities of daily living are utilized to identify those sensors within the plurality of sensors needed to identify each of the activities of daily living above a predetermined quantitative value. Other variants and embodiments are broadly contemplated herein.