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AI and machine learning (ML) advancements enable IoT software developers to include tools that assist organizations in automating repetitive tasks and simplifying workflows related to IoT device management.
Fremont, CA: Internet of Things (IoT) software trends include a focus on cybersecurity and all-in-one desktop interfaces that assist organizations in managing IoT device endpoints and the data collected by these devices.
Key IoT Software Trends
New IoT Software Vendor Revenue Streams
On the vendor side, IoT software providers are generating new revenue streams, which is contributing to the overall market value and growth. More vendors, for example, are entering the infrastructure-as-a-service (IaaS) space, including serving as hosts for other companies' IoT platforms. Instances are MachineMetrics on AWS and Oden Technologies on Google Cloud.
To meet the demand for tools to design, manage, and monitor IoT apps used within organizations as well as revenue-generating apps, vendors are also offering more third-party system integration. End-to-end solutions that can be customized to meet the needs of an organization are also becoming more common. ABB Ability Solutions and AWS Monitron are two well-known companies in this field.
More Machine Learning, AI, and Automation Features
AI and machine learning (ML) advancements enable IoT software developers to include tools that assist organizations in automating repetitive tasks and simplifying workflows related to IoT device management. Machine learning algorithms, for example, can connect sensors to machines, allowing teams to monitor qualities such as equipment condition autonomously, resulting in better predictive maintenance approaches and early detection of issues that could affect production or supply chain logistics.
Machine learning is used in products such as PTC Products' ThingWorx, a platform designed for industrial IoT (IIoT) management, to improve manufacturing processes by analyzing IoT sensor data collected from various points. The platform can then recommend automating workflow processes and improving machine maintenance approaches.