Smart Positioning Technology with AI

Today, AI serves as a crucial driving force behind technological innovation. Aligning with this era, IPIN LABS actively incorporates AI into its positioning technology to enable easier and more rapid productivity enhancements. Particularly for developing differentiated technologies, IPIN LABS utilizes deep learning, especially the ‘self-supervised learning’ approach. This method is a sophisticated technique that demands high computational power. So, why has IPIN LABS opted for this method for location measurement? (For more detailed information about IPIN LABS’ indoor positioning AI technology, please refer to the [previous article].)

Effective Learning Method for Complex and Extensive Data Processing

‘Deep Learning’ is a type of AI technology that learns patterns based on data and excels at predicting or classifying and is particularly effective in solving complex issues such as processing image and speech data. Moreover, IPIN LABS employs an even more advanced learning method, ‘Self-Supervised Learning’, which is pivotal to the AI positioning technology at IPIN LABS.

What is Self-Supervised Learning?

‘Self-supervised learning’ is an approach that directly learns meaningful patterns and relationships from data without the need for separate labeling*. This method is particularly suitable for handling large-scale or complex structured data and plays a crucial role in enhancing the performance of deep learning models. One major advantage of this method is its ability to reduce the costs and time associated with the labeling required by traditional supervised learning, thereby maximizing data utilization.

*Data labeling: The process of adding correct answers (labels) to data to train artificial intelligence models.

Advantages of Self-Supervised Learning

• Reduction in Learning Time and Costs:
Utilizes raw data without separate labeling, significantly reducing the time and costs involved in data preparation and processing.

• Efficient Processing of Large-scale Data:
Self-supervised learning quickly processes large datasets by analyzing the data to identify meaningful patterns and relationships.

• Ease of Data Scalability:
Maintains high accuracy even with partial data use or when the data includes noise.

• Enhanced Generalization Capabilities:
The model learns various patterns from unlabeled data, which enhances its predictive capabilities in real-world scenarios.

Benefits of Applying Self-Supervised Learning to Indoor Positioning Technology

• Enhanced Introduction and Operational Efficiency:
This approach substantially reduces the costs and time required for adopting and updating technology, maintaining continuous performance with minimal management.

• Minimized Infrastructure Requirements:
Thanks to its high data scalability, this method significantly reduces hardware infrastructure requirements, thus easing operational burdens for businesses.

• High Accuracy Maintained in Various Environments:
Demonstrates high adaptability even in complex and variable indoor environments, ensuring precise location measurements.

• Ideal for Large Spaces and Massive Asset Tracking:
Capable of efficiently processing vast amounts of data, this technology ensures accurate location tracking of all assets in expansive spaces.

• Automation of Location Measurement Processes:
Enhancements to the model enable automation of location measurements and model updates.

Improving User Convenience with AI-Based Indoor Positioning

As previously explored, applying advanced AI to indoor positioning technologies can yield significant benefits. Utilizing AI technology is the most efficient method to address challenges that were difficult for existing positioning technologies, such as infrastructure complications due to complex environmental conditions and frequent spatial changes, as well as lengthy deployment times resulting from the vast scale of spaces. AI enables the development of more user-friendly and convenient indoor positioning solutions.

IPIN LABS, in collaboration with AI—the smartest partner—focuses on providing faster and more accurate positioning. The company aims to minimize the inconveniences experienced by actual users and is dedicated to driving technological innovations that lead to substantial improvements in efficiency and enhancements in user experience.