IoT Infrastructure Design Automation Using Manhattan Distance
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Solution Overview
Problem
Existing methods for designing IoT infrastructure are inefficient and prone to errors due to the manual and passive selection of IoT components, leading to delays and incorrect processing, especially with the vast array of components available in the market.
Innovation Solution
A method and system that determine the Manhattan distance between existing and new requirements, calculate relevancy scores, and provide suitable IoT components and designs based on similarity, utilizing a blockchain distributed ledger for secure and efficient component selection and design facilitation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If manual and passive selection of IoT components is used, then design flexibility is maintained, but time consumption increases and accuracy decreases
Solution Approach 1:
The system enables self-service by allowing the automated processing engine to autonomously evaluate IoT components, calculate relevancy scores, and generate infrastructure designs without requiring manual intervention at each step, thereby reducing time consumption while maintaining design quality
Solution Approach 2:
The patent replaces the manual mechanical process of component selection with an automated computational system that uses algorithms to evaluate components, calculate distances, and determine relevancy scores, eliminating the time-consuming manual evaluation process
2Manufacturing precision
If comprehensive evaluation of all IoT components is performed, then design accuracy improves, but processing complexity increases
Solution Approach 1:
The system extracts only the most relevant existing requirements and components by calculating Manhattan distances and filtering based on minimum distance thresholds, rather than evaluating all possible components, thus maintaining accuracy while reducing processing complexity
Solution Approach 2:
The patent transforms the component evaluation process by changing parameters such as using Manhattan distance metrics and relevancy score calculations to efficiently identify suitable components without exhaustive evaluation, balancing accuracy and complexity
3Productivity
If automated processing of IoT components is implemented, then response time improves, but system complexity increases
Solution Approach 1:
The automated processing system is segmented into distinct functional modules including the processing engine, distance calculation module, relevancy scoring module, and design generation module, allowing each to operate independently and efficiently, improving response time while managing system complexity through modular architecture
Solution Approach 2:
The patent introduces intermediary computational layers including the Manhattan distance calculation and relevancy score determination that mediate between raw component data and final design decisions, enabling automated processing to achieve high response times through structured intermediate processing steps
Data Source
AI summary
The disclosure relates to system and method for facilitating designing of an Internet of Things (IoT) infrastructure for deploying an IoT application. The method includes determining a Manhattan distance between each of a plurality of existing requirements and a new requirement, identifying one or more of the plurality of existing requirements corresponding to a minimum Manhattan distance, determining a relevancy score for each of the one or more identified existing requirements based on a similarity between the each of the one or more identified existing requirements and the new requirement, and providing one or more IoT components and one or more IoT designs corresponding to a similar existing requirement for facilitating designing of the IoT infrastructure. The similar existing requirement comprises one of the one or more identified existing requirement with a maximum relevancy score.