From Smart Devices to Wise Decisions: How AIoT Is Transforming Industrial Innovation
For many years, companies within the industry have been working with digital technology, trying to increase the efficiency of their work, monitor their machines and processes. Sensors, connected devices, and cloud platforms have already been used widely in manufacturing facilities, warehouses and logistics. However, despite all efforts of the organizations, they are still facing one important problem – how to use data and turn it into business decisions.
That is why today there is such a concept as integration of Artificial Intelligence (AI) and the Internet of Things (IoT), which is called AIoT, providing new ways to solve problems that are relevant for companies.
Why Traditional IoT Is Not Enough Anymore
In the beginning, IoT implementation was about connection. Organizations used sensors to collect the data from machines and assets, monitoring the processes. The problem is that after that, companies faced difficulties caused by an enormous amount of data.
It is important to have data, but it cannot resolve any issues in business itself; people still have to make sense of reports, spot some anomalies and figure out what to do about them.
AI provides intelligence to IoT-based ecosystems through continuous analysis of large amounts of data and generation of insights, which otherwise would remain unseen. It is a step forward from mere monitoring towards more proactive decision making.
Practical Uses Cases for All Industries
There are many ways how AIoT is already affecting business operations management in various industries.
It has always been an issue for both manufacturers and logistics companies to track their equipment and inventory properly. Using AI to analyze usage and movement patterns is a great way to optimize the existing tracking system.
Better understanding of the company’s physical assets helps to avoid excessive spending, cut down losses and plan the operations better.
Sudden equipment breakdowns often interfere with production plans and incur additional expenses on maintenance.
AI can analyze the performance records and current state of machinery and estimate its probable breakdown. This enables to schedule maintenance before it happens and extend the life of equipment.
Optimization of Inventory
It is quite hard to find the balance and have the correct amount of inventory. Having too much inventory will lead to higher expenses on storing, and having too little will disrupt production processes.
AI will help businesses predict demand better, spot slow inventory, and optimize their replenishing strategy according to their real data.
The industrial area involves complicated machinery and various conditions for work.
With the help of sensors connected to AI, it will be possible to monitor the environmental conditions, identify risks and give advance warnings to avoid any incidents.
Increasing Relevance of Data-Driven Management
In modern conditions digital transformation is not evaluated anymore according to the amount of connected devices in business. The key success factor lies in the ability of companies to use operational data for making decisions.
Now instead of reacting to existing problems companies are learning to anticipate some of them, allocate resources in a better way, and become more resilient.
The transition to predictive decision making is one of the biggest benefits of AIoT.
Building Innovations through Collaborative Approach
For the development of cutting-edge industrial technologies, it often takes skills and knowledge from various industries such as artificial intelligence, Internet of Things, software engineering, and industrial operations. Thus, collaborative innovation approaches become increasingly popular and important.
Venture studios specialized in industrial technology enable the process of building innovations. They are combining technical expertise, market validation, and product development resources. Instead of developing a solution separately, they collaborate with founders, engineers, and partners in order to bring emerging ideas into reality.
Those who would like to learn more about this model of innovation can visit Aperture Venture Studio website.
Combination of AI and IoT opens new ways of thinking regarding operational efficiency, asset management, and industrial innovation. Thanks to intelligent connected infrastructure, organizations are getting a chance to recognize opportunities and act according to real-time insights instead of relying on outdated reports.
Organizations which wisely apply AIoT technology for their needs and do not chase technology just for the sake of it, will probably perform better in the future.
To sum up, data collection is not the future of industrial innovation. Smart and efficient use of data will define it.
Starting as an internal experimental project in 2021 within GAO Group of Companies, Aperture has evolved into a venture studio creating and
