AI, Machine Learning, and Data Analytics in the Smart Home

It is widely acknowledged that the real value from the Internet of Things will be derived from data. Data analytics firms across all vertical markets in the connected home are providing solutions to help companies extract value from data. This report highlights different approaches, AI technologies being implemented, and the associated challenges. It also covers applications that are providing value and company profiles of leading data analytics firms.

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1.0                Report Summary

1.1                Purpose of Report

1.2                Key Burning Questions Addressed by this Research

1.3                Research Approach/Sources

2.0                Beyond Connected to a Smarter Home

2.1                Forms of Artificial Intelligence

2.2                Voice and NLP Drive Growth in the Smart Home

2.3                Data Sources

3.0                Value Chain of Artificial Intelligence Tools

3.1                Public Clouds and AI Development Tools

3.2                Software-as-a-Service/AI-as-a-Service Solutions

4.0                AI Applications in Smart Home Vertical Markets

4.1                Professional and Self-monitored Security

4.1.1            Video Analytics

4.1.2            Audio Analytics

4.1.3            Anomalous Security Behavior

4.1.4            Challenges and Evolution

4.2                Smart Home Automation

4.2.1            Predictive and Personalized Automation

4.2.2            Predictive Maintenance

4.2.3            Challenges and Evolution

4.3                Digital Health

4.3.1            Remote Patient Management and Virtual Care

4.3.2            Independent Living

4.3.3            Chronic Disease Management

4.3.4            Challenges and Evolution

4.4                Energy and Water Management

4.4.1            Learning Thermostats

4.4.2            Home Energy and Water Disaggregation

4.4.3            Appliance Fault Detection and Fire Hazards

4.4.4            Challenges and Evolution

4.5                Secure Networking

4.5.1            AI for Device Identification

4.5.2            AI for Endpoint and Network Security

4.5.3            AI for Parental Controls

4.5.4            Challenges and Evolution

5.0                Implications and Recommendations

6.0                Appendix

6.1                Glossary

6.2                Index

6.3                Image Sources

Simplified Architecture for NLP System
Voice-first Ecosystem
Smart Speaker Penetration of U.S. Broadband Households
Smart Speaker Ownership by Brand
Smart Speaker Ownership by Model
Importance of Smart Home Device Purchase Considerations
Data Sources for AI Applications
AI Stack in the Public Cloud
AI Development Tools
Forecast of Annual Revenue for Professionally Monitored Security (2018 – 2022)
Company Profile - IntelliVision
Appeal of Home and Personal Security Use Cases
Forecast - New Smart Home Controller Revenue by Channel (2017 ? 2022)
DIKW Model of Data Value Extraction
Company Profile – Vivint Smart Home
Company Profile – People Power Company
Trends in Consumer Health Concerns
Number of Connected Health Devices Owned
Company Profile – Care Innovations
Helpfulness of Energy Information
Company Profile – Bidgely
Consumer Concerns about Hacking of Smart Products
Company Profile – Cujo AI
 

Publish Date: 4Q 2018

Pages: 63


Authored By:
Brad Russell - Research Director, Connected Home

© October 2018 Parks Associates
All rights reserved.  No part of this book may be reproduced, in any form or by any means, without permission in writing from the publisher.

Printed in the United States of America. 

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Parks Associates has made every reasonable effort to ensure that all information in this report is correct.  We assume no responsibility for any inadvertent errors.

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