Innovation is crucial for businesses that maintain business relevance and avoid business interruptions, but where will these innovations emerge?
Industry experts believe that innovation will not happen in the cloud, but at the edge. However, edge computing is only an extension of cloud computing. So what does this mean? Because cloud computing and edge computing may work together.
In addition, concerns have been raised about whether the facial recognition technology used in Apple’s recently launched iPhone X will pose greater risks to users’ personal information.
Prior to this, Apple’s smart devices used fingerprint recognition technology, while some Android smart devices adopted iris recognition technology. Therefore, the plot in science fiction quickly became a scientific fact.
Enterprises need to be proactive, especially in dealing with the EU’s General Data Protection Regulation (GDPR) that will come into effect five months later. To ensure that retailers, government agencies, emergency service agencies, and other organizations do not violate regulatory standards, people need to consider whether adopting technologies such as facial recognition, license plate recognition, and vehicle sensors can comply with GDPR regulations and requirements.
Empowering citizens
Jim McGann, Vice President of Marketing and Business Development at Index Engines, has put forward his own ideas regarding these legal provisions: ‘GDPR places the power over personal data in the hands of citizens.’. So, companies operating in the European Union (including the United States) must comply with this regulation. ”
He added that GDPR poses a key issue for organizations to manage their data. Many times, organizations find it difficult to search for personal data in their systems or paper records. And usually they cannot know whether the data needs to be saved, deleted, modified, or corrected. Therefore, due to the potential for significant fines, GDPR will push the responsibility of organizations to a new level.
However, he provided suggestions for adopting relevant solutions: “We provide information management solutions and application strategies to ensure that the organization’s business complies with data protection regulations. PB level data needs to be organized, but the organization does not truly understand what kind of data exists. Index Engines provides services for clearing data by examining different data sources to understand what can be cleared. Many organizations can release 30% of their data, which allows them to manage data more effectively. Once organizations can effectively manage data, they can implement corresponding strategies and measures, as most companies know what types of files contain personal data. ”
Clear data
McGann continued, “Most of the data is very sensitive, so many companies are unwilling to talk about it, but we have also done a lot of work through legal consulting firms to ensure that organizations comply with regulations
For example, Index Engine, a Fortune 500 electronics distributor and wholesaler, completed data cleaning work and found that 40% of its data no longer contained any commercial value. Therefore, the company has decided to remove it.
He pointed out, “This can save the management costs of data centers: they have achieved positive results by cleaning data, but if it is a listed company, data cannot be deleted arbitrarily because of regulatory compliance issues. In some cases, files need to be saved for up to 30 years. He suggested that “companies need to inquire whether these files have commercial value or any regulatory compliance requirements.” For example, if there is no legitimate reason to save data, it can be deleted. Some companies are also migrating their data to the cloud in order to delete data from their data centers.
In this process, many companies need to check whether the data has commercial value in order to make their data migration decisions. Organizations need to consider what is in their files – whether it’s edge computing for data management, backup, and storage, or cloud computing.
Ensure information compliance
Therefore, it is important for organizations to explore how to prevent new technologies from being used in ways that consumers and citizens do not like, and consider how to use this data to create value for the organization and consumers, which is very important. Organizations that use this data need to pay attention to information security in providing, using, protecting, and improving digital services.
For example, facial recognition technology has many applications that not only allow users to unlock applications on their smartphones, but can also be used to pay fees. Through the facial recognition technology of smartphones, their images are saved in locally deployed data centers. However, people still need to retain a certain amount of data on the database, and this data also needs to be protected to prevent hackers from using personal data for malicious attacks.
Innovation in edge computing
With the increasing investment of organizations in autonomous vehicles and smart cities, as well as the development of connected automotive technologies such as automatic emergency braking (AEB), it is also necessary to consider the places for innovation in 2018 and whether a balance needs to be struck between regulatory compliance and innovation.
In addition, more and more people believe that innovation will appear in edge computing rather than the cloud, and edge computing is just an extension of cloud computing. Even if the data needs to be analyzed close to the source, a large amount of data still needs to be analyzed in other places. Data and network latency are historical barriers, and people hope that the impact of latency can be reduced or eliminated.
Edge computing can expand the capabilities of data centers, allowing a large number of smaller data centers to store, manage, and analyze data, while allowing some data to be managed and analyzed locally by a disconnected device or sensor (such as a connected autonomous vehicle). Once a network connection is established, its data can be backed up to the cloud for further action.
Data acceleration
Reducing network latency and data delay can improve customer experience. However, due to the high possibility of data transmission to the cloud, network latency and packet loss may have a significant negative impact on data throughput. Without machine intelligence solutions such as PORTrock IT, the impact of latency and packet loss may suppress data and backup performance.
If the database of facial recognition technology is unable to quickly transmit citizenship and immigration information, this may lead to airport delay, and may lead to accidents or technical problems with autonomous vehicle.
With the emergence of autonomous vehicle technology, data generated by vehicles will flow between vehicles in a continuous manner. Some of these data, such as critical status and safety data, require quick response turnover, while other data is typically road information, such as traffic flow and driving speed. Autonomous vehicle send all safety critical data back to the central cloud location through 4G or 5G networks. Before receiving data, due to network delay, a large amount of data delay may be added during turnover. At present, there is no simple and economical way to reduce latency between networks. The speed of light is the main factor that people cannot change. Therefore, it is crucial to effectively and efficiently manage network and data latency.
The challenge of large amounts of data
Hitachi said that autonomous vehicle will create about 2PB of data every day. It is expected that connected cars will create approximately 25TB of data per hour. Considering that there are currently over 800 million cars in the United States, China, and Europe. Therefore, in the near future, if the number of vehicles exceeds 1 billion, and half of them have full network connectivity, assuming an average usage of 3 hours per day, it will create 37.5 billion kilobytes of data per day.
If, as expected, most new cars in the mid-2020s were autonomous vehicles, then the above numbers would appear insignificant. It is evident that not all data can be immediately transmitted back to the cloud without a certain degree of data validation and reduction. There must be a compromise solution, and edge computing can support this technology, which can be applied to autonomous vehicles.
From a physical perspective, storing an increasing amount of data will be a challenge. The size and scale of data are sometimes very important. This has resulted in financial and economic issues related to the cost per GB. For example, although people believe that electric vehicles are the mainstream of the future, their power consumption is bound to increase.
In addition, it is necessary to ensure that the large amount of data created by individuals or devices does not violate data protection legislation.
November 11, 2021
