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Internet of Things Development Survey 2021, Volume 1

  • ID: 5439275
  • Report
  • September 2021
  • Region: Global
  • 209 Pages
  • Evans Data Corp

This survey gives a comprehensive view of the attitudes, adoption patterns and intentions of developers in relation to the Internet of Things. Evans Data Corporation wishes to make this survey series as valuable as possible to our clients; thus, we solicit input from subscribers prior to the publication of each volume. This subscriber input is incorporated into the content of the survey, providing answers and insight into issues of interest to our clients. Publication rights to any of the results are not granted to any subscribers outside of their own companies without written permission from Evans Data Corp.

Topics include:

  • Demographics and Firmographics
  • The IoT Developers’ Journey
  • IoT and the Enterprise
  • IoT Hardware and Embedded Systems Development
  • Artificial Intelligence and Data Management
  • Cloud Development and Virtualization
  • Edge Computing
  • IoT Development Lifecycle
  • Testing and Performance
  • Security
  • Technology Adoption
  • Automotive and Connected Car Development
  • Wearables Development
  • Data Visualization
Note: Product cover images may vary from those shown

Overview

  • Objectives of the Survey 
  • Survey Methodology 
  • Research Design 
  • Relative Rankings 
  • The Sample - Internet of Things Developers 

About the Author

  • The EDC Panel 
  • Other Evans Data Corp. Services 
  • Multi-Client Survey Series 
  • Custom Surveys
  • Targeted Analytics 

Executive Summary

Demographics and Firmographics 

  • Involvement in Software Development 
  • IoT Development in Moonlighting Efforts 
  • Company Size 
  • Team Size 
  • Company’s Years in Business 
  • Industry 
  • Target Verticals for IoT Deployments 
  • Primary Focus of IoT Development 
  • Outside Sales of Applications  
  • Outside Sales of Applications by Company Size 
  • Monetization of IoT Development 

The IoT Developers’ Journey  

  • Importance of Technologies to IoT 
  • Problems Targeted by IoT Products  
  • Involvement in Tool Purchasing 
  • Initial Information Sources for IoT 
  • Most Effective Learning Resources for IoT Platforms 
  • Characteristics of Targeted IoT Products 
  • Main Factors Leading Developers to Adopt an IoT Tool or Platform 
  • Most Critical Platform Support 
  • Most Helpful Forms of Support for IoT Development Resources 

IoT and the Enterprise 

  • Senior Management Champions for IoT or Mobile Projects  
  • Influencers in Internal Software Projects 
  • Extent of IoT Solutions  
  • Extent of IoT Solutions by Company Size 
  • Scope of Use Cases for IoT Solutions 
  • Scope of Use Cases for IoT Solutions by Company Size  
  • Use of Security Development Teams 
  • Use of Security Development Teams by Company Size 
  • Delivery of Solutions that Manage Devices and Resources as Code 
  • Types of Enterprise IoT Apps that Developers Work On 

IoT Hardware and Embedded Systems Development 

  • Languages Used for Embedded Designs  
  • Top Requirements for Infrastructure and Backbone Support 
  • CPU/Vendor Infrastructure for Device- and Application-level Security  
  • Requirements for Functional Safety Support  
  • Biggest Barrier to Porting Application to a Different Architectures 
  • Most Useful Hardware Development Resources 
  • Most Difficult Issue in Building Connected Devices  
  • Optimization of Real-time Projects for Hardware Architectures 
  • Most Important Hardware Considerations for Real-time Systems 
  • Most Important Architecture Considerations for Real-time Systems  
  • Most Important IP Ecosystem Considerations for Real-time Systems 

Artificial Intelligence and Data Management 

  • Use of Big Data Capabilities 
  • Reasons for Leveraging Big Data in IoT projects
  • Where IoT Data is Typically Used 
  • Types of Database Technology Used as Backends 
  • Timeline for Using AI and Machine Learning in IoT Projects  
  • Use Cases Supported for AI Projects 
  • Approaches for Targeting Hardware with AI Applications 

Cloud Development and Virtualization 

  • Backends Used for IoT Solutions 
  • IoT Middleware Offerings Used  
  • Use of Cloud Services in IoT 
  • Use of Containers for Deployment 
  • Benefits of Using Containers for IoT  

Edge Computing 

  • Top Technical Barriers to Developing Edge Infrastructure Solutions  
  • Plans for Developing Applications for Edge Computing 
  • Percentage of IoT Projects Deployed to the Edge 
  • Workloads Used in Edge Computing 
  • Top Verticals Targeted in Edge Computing 
  • Types of Artifacts Deployed to the Edge  
  • Deploying to Edge Computing Solutions 

IoT Development Lifecycle 

  • Current Challenges in IoT Development  
  • Length of Typical Development Lifecycle 
  • Top Reasons for Delays in Early Development 
  • Delivery of Services via Apps 
  • Obstacles to IoT Innovation 
  • Integration of APIs from Vendors  
  • API Access Features 

Testing and Performance 

  • Optimization for Specific Device Capabilities 
  • Use of Emulators and Simulators 
  • Optimization for Specific Processors
  • Use of Performance and Profiling Tools 
  • Use of Sandboxes for Testing  
  • Use of Video Analytics in IoT Projects 
  • Importance of Physical Factors in Development Efforts  

Security 

  • Optimization for Security 
  • Optimization for Security by Company Size 
  • IoT-Related Security Breaches 
  • Handling of Identity Management 
  • Most Difficult Aspect of IoT Security 
  • Greatest Technical Trouble Spot for IoT Security
  • Most Likely Security Approaches Supported for IoT Apps 
  • Government-mandated Protocols for Authentication 

Technology Adoption 

  • Anticipated Adoption of Emerging Technologies 
  • Reasons for Targeting Emerging Technologies 
  • Plans for Targeting Mobile Devices 
  • Mobile Device Targets 
  • Plans for Targeting Specific Mobile Platforms 
  • Target Platforms for Embedded, IoT, or Edge Design  
  • Sensor Use 
  • Devices Housing Sensors  
  • Types of Sensors Supported 
  • Communication Protocol Use 
  • Connectivity Protocol Use 
  • User Interfaces Targeted for IoT Projects 
  • Technology Adoption 
  • Drivers of Mixed Reality Adoption 
  • Motivations for Selecting Mixed Reality Providers 
  • Top Challenge to Developing Mixed Reality Projects

Automotive and Connected Car Development 

  • Plans for Developing Automotive or Connected Car Software  
  • Likely In-vehicle Platform Targets  
  • Preferred Delivery of Automotive or Connected Car Apps 
  • Interest in Smart Assistants for Auto Deployments  
  • Nature of Automotive Development
  • Plans for Embedded Systems in Automotive Development 
  • Integrating APIs from Telematics Services  
  • Anticipated Connectivity for Automotive Projects 
  • Greatest Challenge in Developing Connected Car Apps 
  • Perceived Leader in Autonomous Vehicles 
  • Barriers to Targeting Automotive Platforms 
  • Barriers to Automotive Platforms by Plans for Automotive Deployment 
  • Greatest Challenges Facing Automotive Development 
  • Automotive Development Challenges by Plans for Automotive Development 

Wearables Development 

  • Plans for Developing Software for Wearables 
  • Type of Wearables Targeted 
  • Initial Wearable Platforms Targeted  
  • Primary Function of Wearables App  
  • Monitoring of Functions in Wearables Projects 
  • End Users Use of Wearable App Functions  
  • Top Concerns for Wearable Device Deployments 
  • Top Challenges When Creating Wearables Projects 

Data Visualization 

  • Involvement in Data Visualization for IoT Projects 
  • End Users of Data Visualization  
  • Delivery Medium for Data Visualization 
  • Roles Responsible for Data Visualization 
  • Important Features for Data Visualization Tools and Services 
  • Data Visualization Metrics Tracked 
  • Commercial vs. Open-source Data Visualization Tools 
  • IoT-specific Data Visualization Tools 
  • Integration of Data Visualization Tools 
Note: Product cover images may vary from those shown

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