Multiple Architectural Approach for Urban Development Using Wearable IoT Devices: A Combined Machine Learning Approach

Raghu T Mylavarapu,Bharadwaja Krishnadev Mylavarapu

doi:10.4236/ait.2018.83003

Raghu T Mylavarapu, Bharadwaja Krishnadev Mylavarapu

Open Access

https://doi.org/10.4236/ait.2018.83003

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Abstract

Machine Learning becomes a part of our life in recent days and everything we do in interlinked with machine learning. As a technocrat, we tried to implement machine learning with Internet of Things (IoT) for better implementation of technology in organizations for security. We designed an sample architecture which will carry the burden of safeguarding the organizational data with IoT using machine learning with an effective manner and in this case we were proposing utilization of cloud computing for better understanding of data storage and retrieval process. Machine learning is used for the prediction models based on which we need to perform high level analysis of data and using IoT we promote authorization mechanism based on which we recognize the appropriate recipient of data and cloud for managing the data services with the three-tier architecture. We present the architecture we are proposing for better utilization of machine learning and IoT with cloud architecture.

Highlights

Machine learning in real-time scenario plays a crucial role and we need to concentrate on how to improve the technical architecture for the security systems with high level data transmission and protection, how the data is transferred from one device or sensor to the repository and how the data is managed and how to get and update the information
Machine learning is used for the prediction models based on which we need to perform high level analysis of data and using Internet of Things (IoT) we promote authorization mechanism based on which we recognize the appropriate recipient of data and cloud for managing the data services with the three-tier architecture
We present the architecture we are proposing for better utilization of machine learning and IoT with cloud architecture

Summary

Introduction

Machine learning in real-time scenario plays a crucial role and we need to concentrate on how to improve the technical architecture for the security systems with high level data transmission and protection, how the data is transferred from one device or sensor to the repository and how the data is managed and how to get and update the information. We need to consider the security measure that how we can utilize the personal data without causing any security bleach [4] In this architecture, we have four stages and in the first stage, we have a sensor which will trap the all the data from the surrounding environment, in the second stage, we have a middleware like a data converter which will convert the data captured by the sensor into human readable language which will be having the combination of IoT and ML. We have four stages and in the first stage, we have a sensor which will trap the all the data from the surrounding environment, in the second stage, we have a middleware like a data converter which will convert the data captured by the sensor into human readable language which will be having the combination of IoT and ML In this phase we need to translate the things using ML algorithms like NLP [5]-[10]. We discuss about the domain of implementation, what are the challenges is highlighted in that domain, in section, we discuss about the individual tiers of implementation, later section deals with the architecture explanation, final section is with expected results and conclusion

Urban Development

Existing Architecture

Wearable IoT Device

Implementation and Results

Implementation Procedure

Conclusion

60 Security