Recently, Avassa, a Swedish edge application management and operation platform provider, completed a new round of investment. In addition to existing investors Fairpoint Capital and Industrifonden, it also welcomed global fashion retailer H&M Group, becoming a strategic investor in the continuous modernization of physical store IT operations.
It is understood that Avassa is a Swedish edge application management and operation platform provider. The company provides platform as a service (PaaS) for managing edge applications and infrastructure in various industries such as retail, industry and automobiles.
This strategic investment further demonstrates H&M Group's commitment to building a new generation of secure and innovative store IT, while further enhancing H&M Group's edge computing capabilities.
Under the wave of digital transformation, with the rapid development of cutting-edge technologies such as big data, artificial intelligence, and edge computing, the retail industry is undergoing unprecedented changes. From supply chain transformation, employment model innovation to consumer experience, innovative business models and other links, digitalization and intelligence are deeply penetrating into all aspects of the retail industry.
On the other hand, with the improvement of people's living standards and changes in consumption concepts, consumers' demand for instant services and personalized experiences continues to increase. In order to maintain market competitiveness, retailers need to keep up with market trends, innovate and improve continuously, and extract valuable insights from massive data to meet the challenges of the rapid development of the retail industry.
However, traditional centralized data processing methods can no longer meet these needs. In this context, edge computing, as an innovative technology, has become an important tool for retailers to enhance their competitiveness with its characteristics such as low latency, efficient processing and real-time response.
Edge computing is a computing paradigm that brings computing and data storage closer to the source of data generation. Unlike traditional cloud computing, which sends data to remote data centers for processing, edge computing processes data on local devices or edge servers without relying on centralized cloud servers. This approach to data sources minimizes latency and enhances real-time processing capabilities.
With edge computing, retailers can maximize the use of IoT devices and the massive data they can transmit in real time, analyze customer data in real time near the data source, thereby speeding up the decision-making process and improving accuracy.
In the retail industry, one of the most typical applications is inventory management, which is an important link in determining the operational efficiency and profitability of an enterprise. In the traditional inventory management model, it often relies on experience and subjective judgment, and is prone to problems such as supply and demand imbalance, excess or shortage.
With edge computing, retailers can monitor inventory in real time, improve inventory utilization, and reduce inventory costs. By deploying sensors and IoT devices in the store to collect inventory data (such as product quantity, inventory location, etc.) in real time, and then preprocessing and analyzing the data on the edge device, the system can quickly identify inventory anomalies and automatically trigger the replenishment process when out of stock, avoiding sales losses caused by out of stock; at the same time, this instant data exchange and processing can also reduce unnecessary inventory backlogs and reduce operating costs.
On the other hand, edge computing has also shown its unique advantages in improving customer experience. By deploying smart edge devices in the store, customer behavior data (such as purchase preferences, stay time, browsing paths, etc.) can be collected and analyzed in real time, and then fed back to retailers to model and analyze consumer behavior data, helping retailers make more accurate marketing decisions, not only realizing personalized recommendations for consumers, but also improving retailers' sales conversion rate and customer loyalty.
In addition, edge computing also plays an important role in scenarios such as smart monitoring security, checkout links, and logistics management. With edge computing, in-store video surveillance systems can be analyzed in real time to improve the security of the retail environment; self-service checkout systems can quickly process payment information by relying on edge computing; logistics data can be pre-processed and analyzed on edge devices to identify logistics anomalies and take corresponding logistics management measures...
It can be seen that edge computing is profoundly changing the operating model and business decision-making of the retail industry. By real-time monitoring of inventory, analyzing consumer behavior, optimizing logistics management, and providing personalized recommendations, edge computing provides retailers with faster and more real-time data processing and analysis capabilities, improves the efficiency and accuracy of business decisions, and helps retailers maintain a leading position in the highly competitive market.
In the future, with the continuous advancement of edge computing, it can be foreseen that edge computing will play an increasingly important role in the retail industry, accelerating the digital transformation and innovative development of the retail industry.
For more information about edge computing, please refer to the "2024 Edge Computing Market Research Report", which is now available for free download in electronic form. Industry professionals are welcome to communicate and correct us! !
This paper is from Ulink Media, Shenzhen, China, the organizer of IOTE EXPO (IoT Expo in China)
