Autonomous Driving

Autonomous driving refers to the capability of a vehicle to operate without human intervention. This involves a complex system of sensors, cameras, and AI algorithms that enable a vehicle to perceive its surroundings, make decisions, and take action accordingly. The level of autonomy can range from level 0 (no automation) to level 5 (full automation).

Autonomous driving has the potential to revolutionize various industries, such as transportation, automotive, insurance, and logistics. It has the potential to improve road safety, reduce traffic congestion, and lower the costs associated with human drivers. Additionally, it has the potential to improve accessibility for individuals who are unable to drive, such as the elderly or disabled.

Currently, autonomous vehicles are being tested in various forms, including self-driving cars, trucks, and delivery vehicles. Some companies and governments have already implemented limited autonomous driving systems in real-world settings. However, the widespread deployment of fully autonomous vehicles is still several years away and will depend on several factors, including regulatory approval, consumer adoption, and technological advancements. While there are many projections, it is widely agreed that the transition to autonomous vehicles will take place gradually over the next few decades.

Smart Robots

Smart robots refer to robots that are equipped with advanced sensors, computing capabilities, and artificial intelligence algorithms, enabling them to perceive and understand their environment and perform tasks autonomously or with minimal human intervention. They can range from simple robots that perform repetitive tasks to highly sophisticated robots capable of complex operations.

Smart robots have a wide range of applications, including manufacturing, healthcare, retail, and transportation. They can provide benefits such as increased efficiency, reduced labor costs, improved product quality, and enhanced safety. For example, in manufacturing, smart robots can work around the clock without breaks and perform tasks with high accuracy and consistency. In healthcare, smart robots can assist doctors and nurses with tasks such as monitoring vital signs, performing non-invasive surgeries, and delivering medication.

Currently, smart robots are becoming increasingly common in various industries, and their use is expected to grow rapidly in the coming years. However, the development and deployment of smart robots are still in their early stages, and significant advancements are expected in the near future. For example, developments in areas such as artificial intelligence, robotics, and sensor technology are likely to increase the capabilities and applications of smart robots. The future of smart robots is expected to be characterized by increased automation, higher levels of intelligence, and the integration of smart robots into various industries and aspects of daily life.

Space Technology

The current advancements in space technology include reusable rockets, the development of small satellites, advancements in satellite communication and imaging technologies, and the exploration of deep space. These advancements have led to increased access to space and have enabled new applications in areas such as earth observation, satellite-based navigation, and space-based research.

Space technology has the potential to have a significant impact on industries and society, including telecommunications, navigation, earth observation, and scientific research. For example, satellite-based navigation systems, such as GPS, have revolutionized the way we navigate and have numerous applications in industries such as transportation, agriculture, and finance. Space-based Earth observation technology has a wide range of applications, including weather forecasting, natural disaster management, and environmental monitoring.

The future of space technology is expected to be characterized by continued growth and innovation. Opportunities in areas such as space tourism, resource exploitation, and space-based renewable energy are expected to emerge in the coming years. Advances in areas such as hypersonic travel, the development of space habitats, and the exploration of deep space are also likely to play a major role in shaping the future of space technology. Additionally, the development of new technologies, such as in-orbit servicing, space debris removal, and the commercialization of low Earth orbit, is expected to drive growth in the space industry and create new opportunities for innovation.

Sustainability Technology

Sustainability technology refers to a wide range of technologies that aim to reduce the impact of human activities on the environment and promote sustainable development. These technologies include renewable energy sources (such as wind, solar, and hydro), energy-efficient buildings, green transportation, and water treatment technologies. Additionally, the circular economy, which aims to reduce waste and increase the use of recycled materials, is also an important aspect of sustainability technology.

Sustainability technologies play a crucial role in addressing global challenges such as climate change, resource depletion, and environmental degradation. By reducing greenhouse gas emissions, promoting energy efficiency, and improving resource utilization, sustainability technologies have the potential to create a more sustainable future for all.

Currently, there is a growing demand for sustainability technologies, and many countries are investing in research and development in this area. Additionally, private companies and organizations are also increasingly focusing on sustainability and incorporating sustainable technologies into their operations. The future of sustainability technology is expected to be characterized by continued innovation and growth, driven by the need to address global challenges and meet the growing demand for sustainable products and services. However, the widespread adoption of sustainability technologies will depend on several factors, including government policies, consumer demand, and technological advancements.

Computer Vision

Computer vision is a field of study that focuses on enabling computers to interpret and understand visual information from the world in the same way that humans do. It involves the development of algorithms and techniques that enable computers to analyze images and videos to extract meaningful information and make decisions based on that information.

Computer vision has a wide range of applications and benefits, including object recognition and tracking, face detection and recognition, image and video analysis, and medical image analysis. In industry, computer vision is used for tasks such as quality control and inspection, and in self-driving cars, computer vision is used for tasks such as obstacle detection and lane detection. In addition, computer vision is also increasingly being used in fields such as security, retail, and entertainment.

Currently, computer vision is one of the fastest-growing areas of computer science, and its applications are rapidly expanding. The development of deep learning algorithms has dramatically improved the accuracy and speed of computer vision systems, and there is growing interest in areas such as augmented reality, virtual reality, and autonomous systems. The future of computer vision is expected to be characterized by continued advancements in areas such as deep learning, real-time processing, and the integration of computer vision into a wide range of devices and applications. Additionally, the increasing availability of large amounts of data, combined with advances in computing power, is likely to drive further innovation in computer vision.

Sensor Technology

Sensor technology refers to the development of devices that can detect, measure, and transmit information about physical or environmental conditions. Sensors can be used to measure a wide range of parameters, including temperature, pressure, light, humidity, and motion.

Sensors have numerous applications across a wide range of industries, including healthcare, automotive, industrial, and consumer electronics. For example, in the healthcare industry, sensors are used for monitoring vital signs, while in the automotive industry, they are used for safety features such as airbag deployment and lane departure warning systems. In industrial applications, sensors are used for process control and monitoring, and in consumer electronics, they are used for features such as touchscreens and motion tracking.

The current status of sensor technology is characterized by rapid advancements in areas such as miniaturization, integration, and accuracy. The increasing demand for wearable devices, the Internet of Things (IoT), and autonomous systems is driving growth in the sensor industry. The future of sensor technology is expected to be characterized by continued innovation, including the development of new types of sensors and the integration of sensors into a wider range of applications. Additionally, the increasing demand for data, combined with the need for more accurate and reliable sensor systems, is expected to drive growth in the sensor industry in the coming years.

Distributed Ledger Technology

Distributed ledger technology (DLT) refers to a type of database architecture that is decentralized, meaning that it is spread across multiple nodes in a network and does not rely on a central authority for management. The most well-known example of DLT is blockchain, which is a secure, transparent, and tamper-proof ledger that can be used to track transactions and other types of data.

DLT has a wide range of potential applications and benefits, including supply chain management, digital identity verification, and the creation of decentralized financial systems. In supply chain management, DLT can be used to track the movement of goods and ensure transparency and accountability. In digital identity verification, DLT can be used to create secure and tamper-proof digital identities that can be used for a variety of purposes. In finance, DLT has the potential to create decentralized financial systems that are more secure, transparent, and efficient.

The current status of DLT is characterized by growing interest and investment, with many organizations and industries exploring the potential applications of this technology. However, there are also challenges to the widespread adoption of DLT, including scalability and security concerns. The future of DLT is expected to be characterized by continued innovation and growth, with increasing use cases and the development of new applications and use cases for this technology. Additionally, the increasing demand for secure, transparent, and tamper-proof systems is expected to drive growth in the DLT industry in the coming years.

Deep Learning

Deep learning is a subfield of machine learning that focuses on the development of algorithms inspired by the structure and function of the brain, known as artificial neural networks. These algorithms are designed to learn from large amounts of data, allowing them to make predictions or decisions based on that data.

Deep learning has a wide range of applications, including image and speech recognition, natural language processing, and autonomous systems. For example, in image recognition, deep learning algorithms can be used to identify objects, people, and scenes in photos and videos. In speech recognition, deep learning is used to transcribe and translate spoken words into text. In autonomous systems, deep learning is used for tasks such as object detection and obstacle avoidance.

The current status of deep learning is characterized by rapid advancements and growing interest, with many organizations and industries exploring its potential applications. The development of large and powerful neural networks, along with the increasing availability of large amounts of data, has led to breakthroughs in a wide range of applications. The future of deep learning is expected to be characterized by continued innovation and growth, with increasing use cases and the development of new applications and use cases for this technology. Additionally, the increasing demand for highly accurate and efficient machine learning systems is expected to drive growth in the deep learning industry in the coming years.

5G/ 6G

5G and 6G are generations of cellular technology that enable high-speed wireless communication between devices. 5G technology provides faster download and upload speeds, lower latency, and increased network capacity compared to 4G, while 6G is the next generation of cellular technology that is still in the early stages of development. 6G is expected to provide even higher speeds and more advanced capabilities, such as ultra-low latency and support for massive numbers of connected devices.

The benefits of 5G and 6G technology include increased speed and efficiency for mobile networks, improved connectivity for internet of things (IoT) devices, and the potential to enable new and innovative technologies and applications. For example, 5G and 6G are expected to have a significant impact on industries such as healthcare, where telemedicine and remote patient monitoring could be greatly improved. They may also drive advancements in areas such as virtual and augmented reality, autonomous vehicles, and smart cities.

The current status of 5G is characterized by growing deployment and adoption, with many countries and regions launching commercial 5G networks. However, there are also challenges to the widespread adoption of 5G, including limited availability in some areas and concerns about security and privacy. The future of 5G is expected to be characterized by continued growth and innovation, with increasing numbers of devices and applications being developed and deployed. 6G technology is still in the early stages of development and it is not yet clear when it will be commercially available. However, it is expected to be characterized by continued advancements and innovations, with the potential to drive significant changes and benefits for various industries and society as a whole.

Edge Computing

Edge computing is a distributed computing architecture that processes data at the edge of a network, near the source of the data, rather than in a central location. This enables faster processing times and reduced latency, as well as improved security and reduced bandwidth usage.

Edge computing has a wide range of applications, including Internet of Things (IoT) devices, industrial automation, and autonomous systems. For example, in IoT devices, edge computing can be used to process and analyze data generated by sensors in real-time, without the need to send that data to a central location for processing. In industrial automation, edge computing can be used to control and monitor industrial processes in real-time, improving efficiency and reducing downtime.

The current status of edge computing is characterized by growing interest and investment, with many organizations exploring its potential benefits and applications. The increasing demand for real-time data processing and the growing number of connected devices are driving growth in the edge computing industry. The future of edge computing is expected to be characterized by continued growth and innovation, with the increasing development of new applications and use cases for this technology. Additionally, the increasing demand for highly efficient and secure computing systems is expected to drive growth in the edge computing industry in the coming years.

Autonomous Analytics

Autonomous analytics refers to a category of artificial intelligence (AI) systems that can analyze and process data, identify patterns and insights, and make decisions based on that information without human intervention. These systems use techniques such as machine learning, natural language processing, and computer vision to analyze and interpret data and provide recommendations or automated actions.

The benefits of autonomous analytics include increased efficiency and accuracy, reduced human error, and the ability to process vast amounts of data in real time. Autonomous analytics has the potential to have a significant impact on various industries, such as finance, healthcare, and retail, where it can be used to improve decision-making, automate routine tasks, and provide real-time insights.

The current status of autonomous analytics is characterized by growing interest and investment, with many organizations exploring its potential benefits and applications. However, there are also challenges to the widespread adoption of autonomous analytics, including concerns about data privacy and security, the need for specialized skills and expertise, and the cost of implementing and maintaining these systems. The future of autonomous analytics is expected to be characterized by continued growth and innovation, with the increasing development of new applications and use cases for this technology. Additionally, the increasing demand for real-time insights and the need for efficient and effective data analysis are expected to drive growth in the autonomous analytics industry in the coming years.

AR & VR

Augmented Reality (AR) and Virtual Reality (VR) are technologies that provide immersive and interactive experiences. AR enhances the real-world environment with digital information, while VR creates a completely artificial and interactive environment. AR is typically experienced through mobile devices or specialized AR headsets, while VR requires a headset that covers the user’s eyes and ears.

AR and VR have a wide range of applications, including gaming, education, entertainment, and training. For example, in gaming, AR and VR can be used to create immersive and interactive experiences. In education and training, AR and VR can be used to provide hands-on and interactive experiences, improving retention and understanding. In entertainment, AR and VR can be used to create new forms of storytelling and experiences.

The current status of AR and VR is characterized by growing interest and investment, with many organizations exploring its potential benefits and applications. However, there are also challenges to the widespread adoption of AR and VR, including the need for specialized hardware, the limited number of available AR and VR experiences, and the cost of implementing and maintaining these systems. The future of AR and VR is expected to be characterized by continued growth and innovation, with the increasing development of new applications and use cases for these technologies. Additionally, the increasing demand for immersive and interactive experiences is expected to drive growth in the AR and VR industry in the coming years.

Read More: The Role of Augmented Reality in the Entertainment Industry

Takeaway

While these technologies offer many benefits, they also present challenges, such as data privacy and security, the need for specialized skills and expertise, and the cost of implementation and maintenance. It is important for organizations and individuals to stay informed about these technologies and their potential benefits, and to carefully consider the potential consequences of their use. Additionally, it is important to ensure that the development and use of these technologies are guided by ethical principles and align with the values of society. By doing so, we can maximize the benefits of these technologies while minimizing their risks and negative impacts.

The post Technologies You Must Put Your Bet On appeared first on Cyfuture Blog.

One of the most exciting applications of AR in entertainment is live events. Imagine attending a concert and being able to see the lyrics to a song displayed in front of you, or visual effects that enhance the performance on stage. AR could also be used to create interactive experiences for attendees, such as allowing them to take photos with virtual versions of their favorite performers.

In the film and television industry, AR could be used to create more immersive and interactive viewing experiences. For example, a movie theater could use AR to project special effects onto the walls and ceiling or to give audience members the ability to choose their own camera angles during a film.

Video games are another area where AR could have a major impact. Imagine playing a first-person shooter game and being able to see enemy positions and other relevant information displayed in your field of vision. AR could also be used to create more realistic training simulations for military and first responders. The use of AR in the entertainment industry has the potential to create unique and engaging experiences that blend the digital and physical worlds in exciting new ways.

What is Augmented Reality?

Augmented reality (AR) is a technology that allows users to see digital information and graphics overlaid on the physical world. This can be done through a variety of means, including smartphone apps, dedicated AR devices, or head-mounted displays.

One of the key features of AR is that it allows users to interact with digital content in a way that feels natural and intuitive. For example, a user might hold up their smartphone and use it to point at a physical object, and the AR app would display additional information about that object on the screen.

AR technology has a wide range of applications, including entertainment, education, and industry. In the entertainment industry, for example, AR could be used to enhance live events, movies, and video games by adding digital elements to the physical world. In education, AR could be used to create interactive lessons and simulations. In industry, AR could be used to provide maintenance and repair instructions to technicians or to create virtual training simulations.

How Augmented Reality Plays a Key Role in Entertainment Industry?

The entertainment industry has been one of the earliest adopters of augmented reality (AR) technology, and it has the potential to revolutionize the way we experience movies, live events, and video games.

One of the most exciting applications of AR in entertainment is live events. AR can be used to enhance concerts, plays, and other live performances by adding digital elements to the physical environment. For example, an AR app could display lyrics to a song as it is being performed, or it could add visual effects that enhance the performance on stage. AR could also be used to create interactive experiences for attendees, such as allowing them to take photos with virtual versions of their favorite performers.

In the film and television industry, AR could be used to create more immersive and interactive viewing experiences. For example, a movie theater could use AR to project special effects onto the walls and ceiling or to give audience members the ability to choose their own camera angles during a film.

Video games are another area where AR could have a major impact. Imagine playing a first-person shooter game and being able to see enemy positions and other relevant information displayed in your field of vision. AR could also be used to create more realistic training simulations for military and first responders.

Use Case of Augmented Reality in the Entertainment Industry

Here are a few more examples of how augmented reality could be used in the entertainment industry:

Music

AR could be used to enhance music festivals and concerts by adding digital elements to the physical environment. For example, an AR app could display the lyrics to a song as it is being performed, or it could add visual effects that enhance the performance on stage. AR could also be used to create interactive experiences for attendees, such as allowing them to take photos with virtual versions of their favorite performers.

Theater

AR could be used to enhance plays and other live performances by adding digital elements to the physical environment. For example, an AR app could display set designs or special effects, or it could provide additional information about the characters and the story.

Movies

AR could be used to create more immersive and interactive viewing experiences in movie theaters. For example, a theater could use AR to project special effects onto the walls and ceiling or to give audience members the ability to choose their own camera angles during a film. AR could also be used to enhance home viewing experiences by allowing viewers to interact with a movie in new and innovative ways.

Video Games

AR could be used to create more immersive and interactive gaming experiences. For example, an AR game could allow players to see digital elements overlaid on the physical world, such as enemy positions or special power-ups. AR could also be used to create more realistic training simulations for military and first responders.

Future of Augmented Reality in the Entertainment Industry

The future of augmented reality (AR) in the entertainment industry is bright, as the technology has the potential to revolutionize the way we experience movies, live events, and video games. Here are a few possible ways that AR could shape the future of entertainment:

AR could be used to create more immersive and interactive live events, such as concerts and theater performances. For example, an AR app could allow attendees to choose their own camera angles or to interact with virtual versions of their favorite performers. AR could be used to create more immersive and interactive viewing experiences for movies and TV shows. It is possible that AR and VR technology could converge in the future, allowing users to experience fully immersive virtual worlds while still being able to see and interact with the physical world around them. This could lead to the creation of new types of entertainment experiences that combine the best of both technologies. As AR technology becomes more sophisticated, it is likely that we will see an increase in interactive entertainment experiences. For example, an AR game could allow players to physically move around and interact with their environment in order to progress through the game. As AR technology improves, it is likely that we will see more immersive entertainment experiences. For example, an AR movie could allow viewers to feel as though they are truly part of the story, or an AR video game could allow players to feel as though they are in a fully realistic virtual world.

Overall, the future of AR in the entertainment industry looks very exciting, with the potential to create unique and engaging experiences that blend the digital and physical worlds in new and innovative ways. As technology continues to evolve, it is likely that we will see even more creative applications of AR in the entertainment industry in the coming years.

Role of Augmented Reality in Other Sectors

There are many ways in which augmented reality (AR) technology can be used. Here are a few examples. However, one should note that these are just a few examples of the many ways in which AR technology can be used. As technology continues to develop, it is likely that we will see even more innovative and creative applications of AR in the future.

Education

AR can be used to create interactive and immersive learning experiences. For example, an AR app could allow students to explore a virtual museum, or it could provide interactive lessons on various subjects. AR could also be used to create simulations for training purposes, such as practicing surgical procedures or learning how to respond to emergency situations.

Industry

AR can be used to provide maintenance and repair instructions to technicians or to create virtual training simulations. It can also be used to assist with tasks such as assembly line work or warehouse management.

Retail

AR can be used to create interactive shopping experiences. For example, an AR app could allow a customer to see what a piece of furniture would look like in their home before they make a purchase, or it could provide additional product information and recommendations to customers as they shop.

Healthcare

AR can be used to assist with medical procedures, such as providing real-time guidance to surgeons. It can also be used to create interactive patient education materials or to provide virtual therapy sessions.

Military and First Responder Training

AR can be used to create realistic training simulations for military and first responders, allowing them to practice responding to various scenarios in a safe and controlled environment.

Transportation

AR can be used to assist with navigation, such as displaying directions or points of interest on the windshield of a car. It can also be used to provide real-time traffic updates or alerts about potential hazards.

Sports

AR can be used to enhance the viewing experience for sports fans. For example, an AR app could display player stats or instant replay footage on the screen of a smartphone or tablet. It could also be used to create interactive experiences for fans, such as virtual meet-and-greets with players.

Advertising

AR can be used to create interactive and immersive advertising experiences. For example, a billboard could use AR technology to display additional information or interactive content when viewed through a smartphone app.

Art

AR can be used to create interactive art installations or to enhance traditional artworks. For example, an AR app could allow a user to see what a painting would look like in different frames or with different background colors, or it could provide additional information about the artist or the artwork itself.

Tourism

AR can be used to enhance the tourist experience by providing information about landmarks and points of interest. For example, an AR app could display historical or cultural information about a building or monument when viewed through a smartphone.

Conclusion

The role of augmented reality (AR) in the entertainment industry is significant and growing. AR has the potential to revolutionize the way we experience movies, live events, and video games by adding digital elements to the physical world. With its ability to create immersive and interactive experiences, AR has the potential to change the way we consume entertainment and could lead to the creation of entirely new forms of entertainment. In fact, it is fast evolving in other industries too at an unparalleled speed. As technology continues to evolve and become more widespread, it is likely that we will see even more innovative and creative applications of AR in the entertainment industry in the future.

FAQs

• How is AR being used in the entertainment industry?
• AR is being used in a variety of ways in the entertainment industry, including enhancing live events, creating more immersive and interactive viewing experiences for movies and TV shows, and creating more realistic and immersive video game experiences.
• What are some examples of AR being used in the entertainment industry?
• Some examples of AR being used in the entertainment industry include displaying lyrics to a song as it is being performed at a concert, allowing movie theater audiences to choose their own camera angles during a film, and creating more realistic and immersive video game experiences.
• What is the future of AR in the entertainment industry?
• The future of AR in the entertainment industry looks very exciting, with the potential to create unique and engaging experiences that blend the digital and physical worlds in new and innovative ways. As technology continues to evolve, it is likely that we will see even more creative applications of AR in the entertainment industry in the coming years, including the convergence of AR and virtual reality (VR) technology, increased interactivity, greater immersion, and personalization.
• How could AR change the way we consume entertainment?
• AR has the potential to change the way we consume entertainment by creating more immersive and interactive experiences. For example, an AR movie could allow viewers to feel as though they are truly part of the story, or an AR live event could allow attendees to interact with virtual versions of their favorite performers. As AR technology continues to evolve, it is likely that we will see even more innovative and creative ways in which it can change the way we consume entertainment.

The post The Role of Augmented Reality in the Entertainment Industry appeared first on Cyfuture Blog.

Having said that, the network and its pipes are just one small part of the IoT universe as a whole – if we take a look at what turns data into gold, it is the uber-fast computing power of the cloud. Creating edge data centers as well as shifting computing to the point of use is when 5G will truly come to life and we will finally be able to deploy IoT at its full potential. The question then becomes, how can data centers evolve in order to accommodate the next generation of users? Even though clients are preparing for 5G technologies and devices, the industry is still working on a definition of what exactly an edge data center is. This is because clients are preparing for 5G technologies and devices.

As data centers evolve, they will be less defined by size and more by proximity to end users and their nimbleness to process, move, and store data.

High-density impact

Machine-to-machine applications and real-time data analytics based on SDNs and network virtualization are the foundation for 5G, which is powered by high-density servers located in today’s data centers. This network of increased computing power has led to hyper-scale data centers and cloud facilities. Those with legacy data centers must (if they haven’t already) migrate to cloud providers or upgrade infrastructure to support future 5G innovations.

As data and network, demands increase, 5G’s impact on data center in India will remain centered around optimizing efficiency, reliability, resiliency, and security.

In addition to consuming more power, generating more heat, and requiring new approaches to how equipment is configured and cooled, next-generation solutions also present conditioning challenges. The cooling system bears the brunt of greater data processing.

Energy-intensive systems have been experimented with to keep cool. High-density computing now uses liquid immersion cooling and direct-to-chip cooling. Water usage effectiveness (WUE) will be given more attention, which is already a hot topic. Chips that need less cooling are an alternative.

Data Center Decarbonization

Cooling and power go hand in hand. They work together to maintain power usage effectiveness (PUE). A high-power-consuming industry will see even more power demands from 5G and IoT. To manage the expected rise in computing power, hyper-scale data centers are already focusing on decarbonization. The green data center market will grow from $49.2 billion to $140.2 billion by 2026. Microgrids, battery storage systems, and hydrogen fuel cells are other initiatives beyond renewable energy credits. Nuclear power, which has a proven track record for innovation hubs, research facilities, and the like, is also gaining interest as a mature, clean technology. A data center near a nuclear power plant or advanced small modular reactors (SMRs) may be used to increase speed to market.

The Rise of the Edge

Increasingly, data centers will be defined by their proximity to end users and their nimble ability to process, move, and store data. In 2025, Gartner predicts that 75% of enterprise-generated data will be created and processed outside of traditional data centers. Providing latency, resiliency, and accessibility to consumers requires a network philosophy and architecture that support storing, processing, and converging near end users.

Data management will be boosted by the proliferation of 5G. Edge will emerge as data gravity becomes stronger, making it harder and more costly to move.

Computing is evolving at the edge faster than the infrastructure can handle, and its proliferation requires smart responses immediately. Edge data management, security, and curation must grow significantly in scale and sophistication to realize machine learning.

Infrastructural hubs make use of existing resources. A natural location for edge data centers can be a geographically interconnected telecommunication tower with access to power and fiber. The companies operating tower sites, such as American Tower and SBA, are actively hosting data centers. Together with Dell and FedEx, Switch, Dell, and FedEx deployed edge data centers and cloud solutions throughout FedEx distribution centers at the end of 2020. With 5G, infrastructure applications will likely be closer to renewable power sources and fiber to support advanced infrastructures, such as autonomous vehicles and industrial IoT.

Accelerating the Edge

There are resources available to make IoT a reality. It is unlikely that one edge data center will be enough to accomplish the job alone. In order to accelerate deployment, owners/ operators must think strategically about designing and building edge data centers that can leverage scale opportunities and speed to market at the same time. Each edge data center will be a unique and customized solution tailored to the organization’s needs and the needs of its location. The success of edge deployments depends on flexible, scalable solutions. Among the most significant factors to consider are:

Understand data requirements

The design of an enterprise’s edge facilities is heavily influenced by latency requirements and the ways in which data will be consumed, stored, and transported. For real-time data analytics and response, will the data be processed and stored in the enterprise or in the cloud? Data centers are designed, located, and sized according to these factors.

Modular, scalable, and flexible design

Data requirements will continue to evolve as 5G evolves. To accommodate the scalability of data growth will require, edge data centers will require modular facilities. Currently, supply chain crunches only make this need more pressing.

Large-scale deployment capabilities

Coordinating a complex network of interdependencies is key to ensuring edge infrastructure deployments are completed on time and within budget. To design, permit, zoning, prefabricate, ship, install, and commission a site, a team of partners and vendors is needed.

Systemwide perspective

Maintaining a consistent customer experience across all locations will require visibility into the entire network of edge facilities deployed and maintained by multisite enterprises. Monitoring and diagnostics of edge operations will be a key focus area for edge owners/operators. 

Read More: Role of AI and ML in improving the performance of Data Centers

Take Away

From site identification and due diligence to permitting, engineering and design, installation and commissioning, consider the entire edge data center deployment process. Owners and operators may wish to hire a project manager and a partner to manage the deployment and mobilize at the required speed and scale.

The extreme dynamics of 5G will continue to be complex for some time to come. Managing this fluid, interconnected web of dependencies won’t go away. Since obsolescence cannot be prevented, everyone involved will need to make a decision about the standard technology philosophy and architecture that will allow for growth and agility. There will always be something new to learn, always something new to pursue, so we need to accept that we will always be behind the technology curve, always trying to stay ahead of the curve.

The post How Data Centers Must Evolve to Enable 5G and Deliver the IoT? appeared first on Cyfuture Blog.

The Telecom Regulatory Authority of India (TRAI) is setting up a high-level forum to draw the roadmap for the launch of 5G network in India. The launch of this technology will make wireless communication speedy up to 10,000 Mbps in cities and 1,000 Mbps in villages.

Source: GSMA Intelligence

Figure 1: The following graph shows the adoption of 4G and 5G smartphones in India, by 2025. Although 5G will create a certain hype in the market, its adoption will be slow growth for the mobile operators. Although the revenue market will grow from $25 billion in 2017 to $30 billion in 2025, with a CAGR of 1.9%, 5G connections will account for only 4.6% of the total connections. 4G connections will grow by 63% of the total connections, in 2025. 

Furthermore, the Global Telecom Industry, GSMA, predicts India to have 920 million unique mobile subscribers by 2025. Out of the humongous number, only 88 million connections will be of the 5G network. Moreover, India will be responsible for generating a quarter of the world’s new mobile subscribers throughout 2017-2025.

Is the Indian Market Ready for the Transition from 4G to 5G?

Source: GSMA Intelligence

Figure 2: The following figure shows the key milestones achieved in the mobile market of India. Mobiles have been a key fuel to the social and economic transformation for India, since 1995. The telecom sector has employed elements that have, in time, acted as the catalysts of the rapid growth of mobile data, paving a way for a digital economy of the country. 

Smartphones, in India, have given birth to a digital economy. They are already playing a central role in deciding the future of many businesses in the country. The new generation of mobile-savvy customers allows mobile companies to realize the true potential of this newly found segment and how to use it for their benefits. With National Digital Communications Policy (NDCP) running campaigns like ‘Connect India’, ‘Propel India’, and ‘Secure India’, challenges related to the 5G network in India need to be discussed and specific investments in this field need to be addressed. 

India has a giant pool of global mobile customers in the market, with more than 750 million unique users at the end of 2018 and the number proliferating to a higher CAGR rate. According to the GSMA Intelligence report, India will hold 1/4^th of the global mobile subscribers in the world over the period to 2025. Furthermore, the market will see a rapid migration from 4G-capable devices and smartphones to the 5G network.

Figure 3: India is leaping very fast to be the world’s second-largest smartphone market. Furthermore, India will strengthen its place as the world’s second-largest smartphone market, after China, by 2025. China will have almost 1458 smartphone connections by 2025 and India will have 983 connections, following the former in the race. The other countries leading the mobile trail will include Indonesia, the US, Brazil, Russia, Japan, Pakistan, Nigeria, and Bangladesh. 

Much of the reason for this prospect is the booming population of India and China and the need for more mobile connections. India already has a highly engaging digital audience consuming all sorts of digital media, services, and content. With the government initiatives to strengthen the hold of 5G network in India, its presence in the digital commerce will be highly profound. 

However, to achieve the high status of being a 5G-equipped country, three things are required; investment in the digital infrastructure, the source of which has to be private companies, a digital environment facilitating this adoption, and a modern version of the policy and regulatory framework to be in place. Although the Indian government is talking a lot about shaping a 5G India, are they ready for such high investment, when reputed mobile companies are withdrawing from the Indian mobile market?

Source: GSMA Intelligence

Figure 4: The following shows the transition of the Indian market from 2G, 3G, and 4G to 5G, by 2025. This shows a decline in the number of 2G connections. Furthermore, the Indian telecom sector will not accept the 5G network, until 2025, owing to the presence of reliable infrastructure and affordability. Also, from 2020 till 2025, 4G connections will be highly adopted by smartphone users. 

Although the Indian mobile piazza is ready to walk on the roads to 5G connectivity, is the Indian government keeping the unique nature of the telecom infrastructure in mind and trying to address the challenges faced by the mobile market of the country?

The question that remains prevalent, still is that the country is not ready for the sustainable footing of a telecom makeover. Furthermore, India is not in its financial capacity to make the necessary investment required for a complete transition to a 5G network. This fact is indeed recognized by the Department of Telecommunications  (DoT) and the Telecom Regulatory Authority of India (TRAI).

Source: GSMA Intelligence

Figure 5: The following is the growth in the 5G smartphone connections worldwide, from 2019-2024. The buzz of 5G has picked up pace only now. The most dominating regions will be the US and East Asia, owing to the rapid increase in the population and the availability of 5G infrastructure. As for India, the market will start developing in 2020 and will grow in numbers from 2025. Until then, only a small percentage of the market will adapt to 5G power and connectivity.

How Well do the Telecom Operations Understand the Prospect of a 5G Network in India?

With the Vodafone-Idea merger enduring their biggest loss of INR 50,921 crores in the quarterly hour, Airtel losing INR 23,044 crores, how well will the India telecom operators work through the 5G wave? 

Before the government starts talking about how fruitful 5G deployment in India is going to be, it is important to note whether the Indian operators ready for the 5G model. The entrance of Jio in the market has affected the telecom industry as a whole. With Jio’s drumbeat of cheap launch offers and tariffs, the Indian audience swept clean of the other telecom operators, switching over to Jio. This annihilation caused by Jio was just the start. It resulted in the ARPU (average revenue per user) drop leading to the consolidation of the entire telecom market. 

The result of it, Jio became the only telecom operator boasting a profit of INR 990 crore in the Q2 2019 financial results, where other telecom operators like Airtel and Vodafone-Idea were compacting on ways to survive through this huge loss in the market. 

While Jio was able to handle this squandering loss due to its rich parent company, Reliance, Airtel and Vodafone-Idea were not able to handle this price drop. This resulted in Vodafone-Idea deciding to backtrack its way from the Indian market. While the existence of established telecom operators in the Indian telecom market is threatened, it seems that thinking about 5G deployment is going to be a futile effort. 

At present, Reliance Jio is the only profitable telecom operator in the market. It claims that it is ready for the 5G ecosystem in the country, and has a network backhaul in place. However, it has voiced its concerns regarding the prices of the 5G spectrum entailed by the TRAI. 

Bharti Airtel, on the other hand, has said that is cannot afford such exorbitant prices and hopes that the government brings them down. The spokesperson also informed that any telco will have to shell out INR 50,000 to INR 55,000 crores for 100 MHz despite knowing that no returns can be incurred in the coming three years. 

Vodafone-Idea merger is the worst hit in the market. It has a debt of more than INR 1 lakh crore, and it feels that they cannot invest in the 5G technology in India. 

Where Does the TRAI Stand in the Context of the 5G Network in India?

TRAI said that it will launch 5G in India in 2020. It released a paper talking about the architecture of the 5G network, policies, the framework, and the challenges of the industry as well. The paper listed 3 key frequency ranges: 

• Sub-1 GHz
• 1-6 GHz
• 6 GHz

Amongst them, 3.5 GHz is named the 5G spectrum around the globe. The DoT is yet to auction the 5G services in India. This means that for telecoms to sell their 5G services in India, they will have to buy the spectrum, and this is where the entire problem starts. The telecom operators market, which is already liquated, suffering through huge losses and high debts, will not be able to spend money on buying a 5G spectrum in India. 

The recommended 5G base price costs INR 492 crores for a minimum of 20 MHz blocks. This means that a telecom company will have to spend around INR 10,000 crore for 20 MHz. This price is released by the TRAI when the Indian telecom market is already under high debt, and they cannot expect a return for such a setup in the next 5 years.

5G vs 4G: The Immense 5G Opportunities in India

Source: GSMA Intelligence

Figure 6: The world indeed belongs to the 5G network. However, for creating such opportunities, telecom industries need to understand various factors. For an effective 5G network to run, you need a supportive policy framework, operator access, necessary infrastructure, and widespread availability of 5G services. Whereas mobile telecom industries might look into the 5G adoption and creating such products, making customers access such services, through the operators is an important task. 

What is 5G? Why it is better than 4G? What makes the 5G vs 4G battle so important? The answer to this question lies in your knowledge of mobile technology. 5G services offer better speed and coverage than 4G networks. It can be described as an advancement in mobile networks, a necessary need of this digital-equipped generation, revolutionizing industries, and consumer experiences. They offer network flexibility which is very much like the need of the hour. Much like the transformations in technology, mobile networks also age and advance. However, such networks require the installation of towers, operators to work on modern techs, newer models of ownership, and network management approaches. The only case in which the 5G network in India can work is when the right raw materials are provided. 

Operators will have to improve their understanding of IoT to expand their enterprise revenues in such fields. Many of the IoT networks are stabilized for 4G networks usage, however, if properly enhanced, they offer better quality service.

Source: GSMA Intelligence

Figure 7:  Indian audiences mainly accesses education-related information, stream live music, and video content through their smartphones.

So, When will the 5G Network in India be Available?

This question doesn’t have any right answer. Because people are still not clear about what 5G vs 4G is all about, and which one is better. With 4G network penetration in the country still accelerating, and the fact that the Indian telecom operators have endured humongous losses, 5G network in India availability doesn’t look like a good picture in the upcoming years.

5G in India might knock the Indian mobile user audiences a little bit later, in 2025, however, one true thing is that the age of low tariffs and affordable local packs are gone. All the telecom operators are now increasing their mobile tariffs by 50%. Such huge changes in price will help the telecom sector to earn some revenue from the market, and maybe bring users closer to the reality of a 5G network in India. 

The post 5G vs 4G: Is India Ready for a Network Evolution? appeared first on Cyfuture Blog.

This strategy in the business world is popularly known as cold calling and it has been a harbinger of good luck for numerous enterprises across various verticals. In call center outsourcing domain, cold calling is often dreaded; the reason being the fact that the outcome on a lot of occasions wouldn’t be as expected.

For instance, if an agent calls someone who is occupied with something important; he might experience the wrath of an annoyed customer. This is really common because we cannot anticipate whether the customer is in the mental and physical condition to consider an offer and respond to it.

In businesses that offer call center services, cold calling is actually both feared and revered. It is feared because who would ever want to deal with agitated customers and revered because of the unanticipated outcome it can offer sometimes. Cold calling just like the door to door sales can help businesses like a call center in India and any other part of the world benefit endlessly.

Cold Calling – How To Make The Best Out Of It?

This is a tough terrain and walking through it is challenging for even the most competent call center outsourcing service provider. Cold calling projects numerous trials, affecting agent and process efficiency at multiple levels. However, when done right, it can boost sales and profits for sure.

For best results, it is vital to understand your target audience and schedule calls as per their availability. It is hard to know the exact time when your customers might be available to take the call but it is best to not disturb them in evening or nighttime.

A lot of call center service providers run cold calling processes in multiple shifts, which may or may not be a lucrative decision. In the evening and at nighttime, people want to relax and unwind; so, disturbing them at this time isn’t advisable.

The best time to make a cold call in the evening is between 4 to 5 PM because this is the time when everyone is winding up their work or having a cup of tea or coffee to relax. This is the time that they might listen more attentively and respond in a better way.

In the morning, the best time to call your prospected customers with reliable customer support service is between 8 to 9 AM. This is when people are about to start their day and are usually in a good mood, which is why they tend to give more attention to every call, even the ones that are meant for sales purpose.

Go4Customer is one of the most credible businesses in the outsourcing domain. It is known for offering a varied range of call center services including cold calling. So, in case you wish to avail them then get in touch right away.

The post Boost Sales & Profits with Cold Calling appeared first on Cyfuture Blog.

1) Evolution in the Internet of Things (IoT) space:

The Internet of Things (IoT) is a system of interrelated devices, mechanical and digital machines or objects which are provided with unique identifiers and can transfer data over a network without requiring human-to-human or human-to-machine interaction.

Connected devices and sensors in IoT space generate an enormous amount of data every day. It is estimated that by 2020 there will be over 10 billion connected IoT devices.

In order to milk the maximum benefit from the data flowing in from these devices, Big Data solutions would be required. Big Data systems can store, process and analyze heaps of data using specialized tools like Hadoop or Spark to unveil valuable trends, patterns and correlations.

Informative Blog: Is Artificial Intelligence Really a Helping Hand for the Healthcare Industry?

IoT devices have already invaded many aspects of our lives. Smart homes, smartwatches, smart cities and Industrial IoT have become the latest buzzwords in the technology sector.

a) Smart Homes:

The smart home concept is slowly catching up and companies like Nest, Ecobee and Ring are coming up with a range of innovative solutions for modern era home-owners.

In a smart home, the appliances and devices are interconnected and can be controlled remotely through one central point, which may be a smartphone, tablet or laptop. These devices can optimize and control several crucial functions like security access, temperature, lighting and home theatre. Locks, thermostats, cameras, lights and even appliances such as televisions and refrigerators can be controlled through a home automation system.

Check Out: Machine Learning – A New Wave of Intelligent Automation

Companies can deploy appropriate Big Data solutions to harness this data to track consumer behaviour, improve customer experience and eventually enhance customer loyalty.

b) Wearables:

The rapidly expanding market for wearables such as Apple Watch and Fitbit has provided an opportunity for healthcare professionals to collect patients’ data in real-time and prescribe the course of action.

These wearable devices can track vital health metrics of a patient such as steps taken, heartbeat, quality of sleep and/or blood pressure. These can used as inputs in Big Data systems to monitor the patient’s health closely and address risk factors on time.               

An important example in this regard is Epiwatch, an app developed by Johns Hopkins University to collect data of patients before, during and after an epileptic seizure. The app works on both Apple Watch and iPhone, and uses memory games and other activities to collect vital information on the health of epileptic patients. Researchers at John Hopkins have been using the information thus collected to predict and report seizures.

c) Industrial IoT:

With IoT becoming more ubiquitous, industries such as oil and gas, utilities, manufacturing and transportation have embraced it and are coming up with innovative applications. Big Data can empower industries to harness maximum value from the data gleaned from IoT sensors and devices. Manufacturing companies, for instance, use the data collected from sensors installed in plants to predict and schedule preventive maintenance and thus improve equipment lifespan.

By using Big Data in collaboration with IoT, businesses can have a better understanding of their data; they can make more informed decisions and stay ahead of the competition.

2) New, exciting roles in the IT industry:

Now that Big Data has become more central to the functioning of organizations, newer roles are coming up and companies are trying to rope in competent Big Data professionals in order to make the most of the data available to them. Some of these roles are:

a) Data Scientist:

A data scientist uses descriptive and predictive analytics to deconstruct large sets of data and communicates the results to different functions of an organization such as marketing, operations or IT. The role needs a high degree of proficiency in languages like Python, SAS or R, a thorough understanding of advanced statistical and machine learning techniques and an excellent working knowledge of platforms like Hadoop and Apache Spark.

b) Data Engineer:

A data engineer is one who develops, tests and maintains infrastructure (i.e. architectures and systems) which drives analysis and processing of data. They develop processes for data modelling and mining, integrate new solutions into production systems and ensure that the architecture supports business requirements. A data engineer needs to work in close collaboration with the data scientist as well with the IT team.

In coming times, newer and more exciting roles, such as Chief Data Officer will be in demand across all verticals. This will provide an opportunity to professionals to learn new technologies and flourish in the Big Data space.

3) Emergence of Dark Data and its Migration to Cloud:

Given the immeasurable volumes of data that organizations collect, it should come as no surprise that a large chunk of their data is not processed and analyzed.Research giant Gartner has labelled this data as ‘dark data’.

According to a study by the International Data Corporation, an estimated 90% of the unstructured data goes unanalyzed. Organizations seldom process several categories of data such as customer information, archived e-mails, call logs, hand-written notes, old documents and website visitor behavior, and there are solid reasons behind their failing to do so.

In many organizations, different departments have their own data collection and storage processes which are usually not known to (and, therefore, not utilized by) other departments.

A lot of data goes unused in this way. Then, there may be technological constraints (e.g. difference in file formats) in integrating data from different sources in order to paint a more holistic picture. Most of the companies have pre-decided goals before data collection and may not use the data not directly related to their end-goal.

For example, a company trying to collect employee feedback through an analytical tool considers only existing employees and disregards any information from previous employees.

This unutilized ‘dark data’, if analyzed, can provide eye-opening insights, unravel hidden patterns, and in many cases, decide the future course of action. Inability to manage sensitive data, such as customer information can throw a company into legal and financial turmoil and even cause a loss of reputation. Majority of the organizations are, therefore, migrating this data to the cloud until its best usage can be determined.

4) The Dominance of Open Source:

Till now, the Big Data space has been dominated by open source tools and technologies, and the trend will continue in 2019 and beyond. Open-source software framework Hadoop has become almost synonymous with Big Data. Hadoop is known for its large-scale distributed processing of very large datasets.

Another renowned name in open-source space is Storm, an engine for real-time processing of Big Data that behemoths like Yahoo, Twitter and Spotify have leveraged to their advantage. Open-source platforms, be it MongoDB, an open-source non-relational data storage solution or Lumify, a Big Data analysis and visualization platform or Jaspersoft, an open-source BI tool, have become central to the functioning of organizations across the industry.

Given the exponential rate at which data is being generated, more open-source tools would be made available soon. This will be particularly beneficial for small and medium-sized organizations that look for pocket-friendly solutions for data storage and processing.

5) Cybersecurity Opportunities and Threats:

The growing pool of Big Data has opened up new avenues of attack by cybercriminals who have developed more sophisticated methods of data breaching of late.

Technology-savvy criminals exploit machine learning algorithms to detect vulnerabilities in the security system and bypass security software. Traditional cybersecurity tools which were once considered effective are now becoming obsolete. These tools have been more reactive than pro-active in approach, rendering them unsuitable for current times. Besides, they lack the bandwidth for very large datasets.

Companies need robust cybersecurity measures in place as they have to safeguard personal and sensitive information (e.g. their customer database) and deal with data ownership and/or copyright infringement issues, if any.

Cybersecurity experts have kept pace with the changing times and are coming up with advanced threat detection methods such as behavior analytics and machine learning. Machine learning models are trained on voluminous datasets multiple times in an attempt to automate threat detection using supervised and unsupervised learning techniques.

Supervised learning techniques make use of labelled datasets and train the model to distinguish malicious files from benign ones.

Unsupervised learning techniques, on the other hand, use unlabeled datasets and teach the model to pinpoint anomalies in the data. These techniques, coupled with human discretion, will go a long way in building a robust cybersecurity system.

The Bottom Line:

Given the pace at which the Big Data industry is transforming, organizations need to ensure that they stay abreast of the emerging trends in this space and put in the needed resources to extract maximum value from their data! Cyfuture takes this proactivity to the highest levels!

The post Emerging Trends in Big Data for 2019 and Beyond! appeared first on Cyfuture Blog.

Artificial Intelligence has made the leap from science fiction to real life in a short matter of time. It was initially envisioned as a panacea for the intricate but repetitive processes that aided scientific research and technological advancement – a role it has fulfilled and, in many instances, surpassed.

Training a program by making it understand a variety of sensory inputs, whether in the form of digital or analog data, does not mean that program has ‘intelligence’. The result of this factor being used to decide the intelligence of software leads to various technologies that were quite revolutionary at their inception now being classified as routine programs, because their previously groundbreaking tasks have become rudimentary in today’s advanced day and age.

A Brief History of AI

Automation has been a pursuit of humanity since classical Greek antiquity. The word ‘automaton’ itself is used by Homer to refer to machines acting according to their own will. There is ample evidence in literature and history that shows how we have striven to recreate machines that not only look like us, but walk, talk and act like us. The more successful efforts towards such aims are said to be in the ‘uncanny valley’, an uncomfortable state which results from the almost, but not entirely, accurate depiction of human beings by doppelganger machines.

Interesting Article to Read : Chatbots & Live Chat | A Sprint to Sublime Customer Service

Alan Turing was instrumental in making artificial intelligence a practical field. Approaching AI in purely mathematical binary terms, digitization was used as the platform to erect expert systems, which use inference engines and knowledge bases to make decisions. Moore’s Law, which predicted computing power rising up while component sizes reduced, still remains applicable, albeit to a slightly lesser extent.

Now, with data surging forth from all sorts of sources right from our handheld devices to astronomical observations and literal rocket science, machines that have been developed specifically to ‘think like a human’ are rapidly being deployed in a variety of fields, form bioengineering to synthetic medicine. Nearer our daily lives, search engines [one (followed by a hundred zeros) in particular, but all of them in general] and flagship smartphones use all the learnings gleaned from AI to deliver ‘personalized experiences’ right into our hands!

We Are Already AI-ed, Daily!

In 2014, Stephen Hawking gave a subliminal quote on AI: “It [AI] would take off on its own and redesign itself at an ever increasing rate. Humans, who are limited by slow biological evolution, couldn’t compete and would be superseded.”

While such a day still seems far off as of now, the quest for replicating human thought patterns and response heuristics continues unabated. Programmers in diverse fields toil away every day at their projects, attempting to reproduce the thought processes that make up the human mind. They have to take many factors into consideration, not the least of which is the ethical complication in ‘fooling’ a human into thinking they are conversing – or, at basic levels, interacting – with a machine.

We are already carrying out a great deal of everyday interactions with artificial intelligence. The level to which it affects the technology in the palm of our hands is difficult to identify at the user level. To delve deeper, we have to break down the integral components of interactions amongst humans and machines – a task easier said than done.

The question I asked at the beginning is hard to answer, because it is rooted in the future. At Cyfuture, we are accustomed to asking questions that require a certain kind of ‘never giving in’ mindset to answer – for laterally solving problems or creating innovative solutions to increase the effectiveness of existing legacy systems, as well as drive businesses better.

The post AI: Can A Machine Ever Be Human, Convincingly?  appeared first on Cyfuture Blog.