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How IoT Boosts the Micro Mobility Market

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December 8, 2022

How IoT Boosts the Micro Mobility Market?

The Internet of Things is no new thing in the tech market. Just look around, and you’ll find that most of the gadgets and comfort offering solutions are connected to IoT. One of the most popular and known solutions is your virtual assistant,” Alexa.” The way that device handles other internet-connected devices in our homes is incalculable. But limiting the character and usefulness to just these things would be unfair. IoT is also immensely used in logistics, manufacturing, industrial automation, and many others. Not just this, IoT is also being used in the micro-mobility sector.

Any idea about micro-mobility?

The word micro-mobility directs to lightweight transportation for individuals. It shields different transportation options that weigh less than 500kg (1200 lbs).

Some examples are electric scooters, bicycles, e-bikes, segways, electric skateboards, etc. Micro-mobility is very different from vehicles that are used for long distances. It focuses on short distances and generally for less than five miles. There are considerable advantages to the micro-mobility market, which is the reason behind the huge investment made by tech giants. In 2020 investment in the micro-mobility market was $800 million. This scenario rocketed after the lockdown restrictions were removed. The micro-mobility brands drew around $2.9 billion in 2021.

Advantages of the Micro-mobility Market:

Let us know three specific benefits of the micro-mobility market that support these high investments:

1: Convenience

One of the most popular and justified benefits is convenience. Transportation options can help customers reach their destination early and with comfort.

2: No Parking Issues:

Parking is one of the major issues in big cities, but micro-mobility can solve this problem. You will never again face parking issues by using micro-mobility transportation choices like segways and hoverboards.

3: Cost-Effective:

As micro-mobility involves ride-sharing, it will automatically become cost-effective; you can rent without requiring any license for hoverboards or e-bikes.

Challenges Faced by the Micro Mobility Sector

The idea of micro-mobility appears appealing, but some challenges hinder the growth of businesses. However, there is zero to be upset about as long as IoT exists, as it has the potential to advance the micro-mobility market.

Data Sharing:

Suppose your own a firm that has 100 ebikes throughout the city. People take your ebikes but pay less attention to the charging levels, and why would they? They are your service bikes, and it’s your responsibility to take care of them. Well, not just this, there are many other issues like ending the ride midway, navigation issues, leaving the vehicle anywhere, and overriding the ebike that can cause damage and revenue loss.

Therefore, there is a need for a solution to collect all the necessary data about the vehicle from time to time. With IoT-connected devices like highly sensitive sensors, one can quickly get all the data related to the vehicle for analysis and make informative decisions. Moreover, adding IoT sensors will also make it manageable for you to transfer data with the traffic authorities to watch vehicle activity in a good way.

Riding Behavior:

It is pretty noticeable to see people riding aggressively on the road. This can be inspired because of different reasons like road rage or time-saving. However, no reason justifies the purpose as it can distract or put other’s life at risk. With IoT sensors installed on the vehicles, businesses can check the vehicle status and warn the rider by sending messages.

For instance, if a person is riding at high speed or cutting the lane often, sensors can record the data and share it with the related authorities for further action. This can protect vehicles from damage and save companies from getting banned due to abnormal riding behavior.

Safety:

Whether a car or a scooter, safety remains the top priority for micro-mobility service provider companies. It is essential to integrate features that protect the riders. These added features are not just limited to safety but also allow businesses to meet government requirements to secure their business.

Theft and Vandalism:

A micro-mobility company’s worst loss is when a vehicle is damaged or lost. Therefore, it is necessary to install proper security measures to prevent this from happening, and yes, IoT can help with this. By implanting a few IoT sensors, companies can stop stealing ebikes. Additionally, these sensors can also be connected to other systems to initiate warning messages.

If it is a genuine user, they can use their phone to get an OTP and use the ebike. Further, the vehicle can have environment-mapping sensors to prevent vandalism.

Scaling Service:

IoT can help in business scaling, but the critical challenge with IoT is that one needs to modify the complete system to upscale instead of a single one. The most feasible option is to get the most suitable IoT service providers. A single service provider will promise smooth and seamless scaling as the operator would have knowledge of your business operations.

Compliance:

Compliance with government standards and norms can hinder growth as they may change and be difficult to follow. However, if state-of-the-art IoT solutions back you, they can become more accessible. IoT sensors can be employed to keep riders stay within speed limits. It can guarantee that vehicle is parked at the right spot. In fact, smart sensors can also guide the riders to the nearest charging station. These criteria also guarantee that riders do the right thing and that government norms are obeyed.

IoT and Micro-mobility

IoT can support the upheaving micro-mobility market, but the only condition is that this will demand colossal investment. Once an investment is made, all other systems are managed, and only timely maintenance and upgrade is left. Investment in IoT for the micro-mobility sector promises a better future and benefits, and various tech giants like Uber and many others are forwarding toward it. This shows that micro-mobility holds a great scope in the coming years. It not just brings transportation at ease but also promises its contribution towards the environment by reducing the dependency on crude oils. The integration of micro-mobility with IoT makes it safe and futuristic.

Connecting Industrial Protocols and the Cloud

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November 22, 2022

Why Connect Industrial Protocols with Cloud

Industrial protocols are conversations between industrial automation products for data collection or control. At the beginning of industrial automation, communications were a competitive differentiator, and automation vendors developed communication protocols to leverage technical advantage and lock in their customer base. It has changed with time; today, vendors have extended their protocols and even designated them industry standards to boost adoption. Vendors acknowledged that suppliers with the largest ecosystem of products to choose from, would have a better livelihood of winning parts of a project, if not the complete project. Vendors also learned that it is challenging to be a specialist in all areas of automation. Let’s find out different industrial protocols and those that can be compatible with cloud applications.

Different Types of Industrial Protocols

With time, the manufacturing marketplace has become prevailing by a set of protocols, possibly from the leading suppliers of automation products. Before examining the best-suited for the cloud, let’s know some of the most common industrial protocols. These include protocols such as Modbus, Profinet, CC-Link, Ethernet IP, etc. Many of these are present in different forms to acknowledge varying topologies and purposes eg-dedicated wires vs. Ethernet.

Attempt to bring standardization over the years fetched technology from the OPC Foundation, which was originally Microsoft technology-based, using COM and DCOM Windows technologies for communications between applications. Hence, OPC (OLE for Process Control – OLE that is, Object Linking and Embedding – the technology after COM) is delivered.

1: OPC

OPC obtained standards for accessing data, either subscribing or polling, and the purpose of different data types and how to manage them (Analog and Discrete variables, History Data, Alarms, and Events, among others).

In time, this standardization endeavor shifted from windows technology-centric to operating system-agnostic to aiding Linux and delivering functionality that would be useful to Internet-based communications.

2: OPC UA

The new standard was recognized as OPC UA- with OPC now representing Open Process Communications and UA representing Unified Architecture, one standard to supersede the previous standards that had developed.

3: MQTT

Another technology that is more concentrated on the transfer of messages and less on the content of messages generated out of the need for a very distributed infrastructure with limited bandwidth, as found in the upstream oil and gas market. This protocol is known as MQTT. It is used in the industrial automation marketplace, specifically for cloud communications, and has become very popular in recent years.

4: BACnet

The vertical market shows unique requirements and has supported the requirement for unique developments. BACnet is the leading protocol in the Building Automation Systems (BAS) space. In the Power Generation and Distribution Space, several protocols like IEC-61850, 60870, and DNP-3.

Over time, these protocols have survived on various topologies, and today most of them offer Ethernet compatibility.

Why is the Cloud So Important?

The advantages of cloud computing are numerous and stimulating. They possess:

Transformation of capital expenditures to operational expenditures
No need to concentrate on infrastructure management
Benefiting a constantly scalable architecture
Furnishing accessibility to your absolute organization, anywhere and anytime
Benefiting services from domain experts (security, upgrades, solution development)

The cloud can endure different forms, from a solution delivery by industry leaders like Microsoft and Amazon to more scaled offerings for targeted markets. Ultimately, there are hosted solutions, pushing on-premise servers to virtual servers in the cloud, but fully controlled by the IT staff of the organization.

The objective of cloud computing is to provide a lower total cost of ownership by reducing expenses in system management and hardware ownership and the capability to take advantage of solutions offered by others. These third-party solutions are usually built for market purpose and provides multi-tenant capability, letting the service provider handle many customers whilst offering data and user isolation. The concept of cloud computing, specifically for the industrial marketplace, is still in its initial stage, and businesses are fighting with cloud connectivity and the idea of hosting their data to the outside world.

However, the benefits are convincing as it reduces operating costs, and domain experts have developed vertical market applications that require connectivity to the correct data. Additionally, service providers can utilize knowledge gained over their extensive array of customers and offer great value to an individual customer. So, the failure mode of a product in an environment can be predicted by learning about the failure mode in other environments. It helps in potential predictive analytics tuned by the results and anonymization of data from a similar ecosystem of users. While connecting to the cloud, evaluating which industrial protocols best suit the application is necessary.

Things to Consider When Connecting to the Cloud

The best attributes offered by cloud-based solutions fall into two main categories:

Security ( including access security and cybersecurity)
Transmission (the quality and reliability of data)

Security is mainly managed using VPNs (Virtual Private Networks). It is an excellent way for bi-directional and ad-hoc communications as it is designed for remote troubleshooting. Using VPNs for ad hoc access, customers can use solutions to secure and broker access to endpoints in a very organized and controlled way. It includes approval processes, windows of access and time limitations, and extra levels of authentication.

For information communication to the cloud, it is becoming more prevalent to utilize public-subscribe models and connection brokers to enhance security. Remote sites will share data to a tight and secure connection. The users of data and cloud applications will subscribe to the data through a broker, eradicating application knowledge of remote communication details that illustrate an exposure. Microsoft IoT Hub is the best example of this technology.

Industrial Protocols for Cloud Connectivity

It is optional that all industrial protocols are compatible. Without knowing each protocol and determining if it can be integrated into a cloud, a complete solution to the connectivity issue is to add edge device technology. It will manage the communications to the IT and OT environment and the need for cloud data transfer. Their devices are now covering the market with specific cloud connectivity or a toolkit approach that can be eased their configuration. Most of them are designed with data transfer as their primary function, whereas others support data modeling, visualization, and analytics, in addition to data transfer.

Ethernet is also improving with time in both topology and performance. A more visible improvement is device synchronization and the power to shape traffic. These attributes and other things are Ethernet enhancement called TSN (Time Sensitive Networking). TSN promises the skills to prioritize communications on Ethernet and control traffic bandwidth.

Connecting Safely and Securely

With the expansion of industrial protocols in the market, it is now feasible and easy to connect virtually any automation solution to the cloud with complete privacy, directly or using edge gateways.

How Artificial Intelligence in the App Industry is Changing the Future

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November 3, 2022

How Artificial Intelligence in the App Industry is Changing the Future

“Artificial Intelligence is no more in fiction stories now. Today in our daily life, we can observe AI performing different tasks.“

Even if it is a customer or business organization, machines are vigorously improving the intelligence of humans. The mobile app sector is growing day by day. After the covid hit the world, it has become the basic need of many companies. For customers, it has become a way to reach the maximum number of things through the mobile application. With the involvement of AI, it is changing at an incredible pace, and the users get the best use of the app to meet their basic daily needs.

What is Artificial Intelligence?

It is a system capable of imitating intelligence and behavior to work and act like humans. It is possible because of some of the algorithms. It provides a virtual assistant without any human intervention. AI delivers predictive messaging, learning and planning capabilities, and voice recognition that will assist in understanding the language. It holds impressive skills in solving problems. It just does not work for business organizations but also magically works for customers. It fetches the best solution to help your business flourish and build a strong customer relationship.

Benefits of AI

It provides the best output of investment where the marketers will receive essential feedback from the users. Digital marketing for all kinds of businesses guarantees that return is always two-way. Both customers and organizations should get the return they expect to survive in the competitive tech world.
AI also assists in developing customer relationships. It is challenging for an organization to personally connect with each customer’s problem. In such cases, AI works as a savior. Whenever the user reaches customer service on the app, AI offers incredible help and gives the most-suited solutions to the users. Therefore, creating a good relationship with the customer.
AI also enables the company to make a fast decisions on any strategies. It assures that the company can access real-time situations; AI provides qualitative customer and business decisions. It is the most convenient way to connect with the process and gain success in the field.
Market measurement plays a crucial role in the business. AI offers the best market measurement where the company is aware of the risks and benefits of an issue.

Here are the following ways through which AI is supporting the mobile app industry:

Internet of Things (IoT):

Today, many devices are connected to the internet. If not mobile, the internet connects with a fitness tracker, kitchen appliances, watch, TV, etc. The connected device collects user activity data and provides powerful insight. Both AI and IoT work together so that customers get the most enhanced experience. With the support of digital assistance, the developer is able to develop an app that will easily connect to the TV.

AI is connected with sensors in broad options and offers a location-based experience. AI is most appreciated in app development and is helpful in building the best app.

Automation development:

Development of the app demands excellent skills. In the process, many tasks are to be completed, which eats up time many times. However, by using AI, the development team can easily save time as well as money that can be used to automate the process. Not just this, AI can provide consistency and eliminates errors. AI can also help in skipping the repetitive tasks and mistakes caused by it.

AI chatbots:

When you visit any website, you’ll see a chatbot below the website. If you click on the chatbot and fill in your details, AI will identify your need and pattern and reply accordingly. If your problem has a solution, AI will immediately solve it and give sales support and customer service.

Understand user:

Selecting the clues from the users, AI comprehends what the users need and assure that they get the same thing. It analyzes the activities and behavior of the user and provides the best suggestions. Additionally, they can understand the user’s behavioral patterns and apprehend the users’ needs.

Personalization service:

We all know that every customer’s need is different from each other. Therefore, customization is the best way to offer customer satisfaction and will boost sales. The modern AI service will ease the work of developers and offer the best-customized services. AI detects the customer’s pattern, taste, or preference. It suggests the same interest and preferences so that customers get engaged and shop from the options.

Mobile App Industries that use AI to change the future

Healthcare App:

Now, healthcare services are just a dial away. You can get the best healthcare services at home and receive the reports in your mail. With the inclusion of AI in services, a patient’s medical details are now collected, stored, and managed efficiently.

Automotive App:

In the automotive sector, all the brands are embracing the latest vehicles where Artificial intelligence enhances the driving experience. While driving, one can use AI features for navigation and listening to music. Driverless cars are next-level features offered by AI.

Finance App:

In the banking sector, AI is helping customers to save money by educating them on where to invest. It assists them so that they can track their expenses and manages everything on points. It assures that finance sectors can help customers in solving their problems while sitting in their homes.

Law App:

Sometimes it takes work for attorneys to answer all the questions in person. In that case, AI can help by answering all the legal questions to clients so that they get answers to all their doubts.

Conclusion:

Though Artificial intelligence has its challenges, it still never fails to improve the app industry. Today, many app owners in various sectors are using this technology to stay updated with the trend and customers as well. AI ensures they can create a good relationship with the customers by recognizing their behavioral patterns in shopping or anything else. Therefore we can conclude that Ai is more than a technology. It is a blessing for app owners to develop a good relationship with customers.

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October 13, 2022

How can Artificial Intelligence Boost the Manufacturing Industry?

Today, most of the Giant industries, around 83 percent, believe that AI delivers better outcomes; however, only 20 percent have embraced this technology. It is pretty clear that a stronghold on the domain is important for successfully adopting artificial intelligence in the manufacturing industry.

Domain expertise is important for successfully adopting artificial intelligence in the manufacturing industry. Jointly, they form Industrial AI that uses machine learning algorithms in domain-specific industrial applications. AI can be potentially used in the manufacturing industry through machine learning, deep learning, and computer vision.

Let’s check out some of the critical needs in artificial intelligence technologies in the manufacturing industry to obtain a better picture of what one should do to keep the business up-to-date and seamless.

AI Is a Broad Domain

Artificial intelligence is not the correct way to describe all the technologies, and we’ll discuss that they have applications in manufacturing industries. AI is a big subject with different methods and techniques that fall under it.
There are robotics, natural language processing, machine learning, computer vision, and many other technologies that also need attention.

Keeping this in mind, let’s begin with artificial intelligence applications in the manufacturing industry. So here are some industrial uses of AI.

The Goal of AI in Manufacturing

Artificial intelligence studies how machines can process information and make decisions without human interference. The best way to understand this is that AI aims to mimic how humans think but not necessarily. We all know that humans are better and more efficient in performing certain tasks, and in certain tasks, they are not. The best type of AI is one that can think and make decisions rationally and accurately. The best way to explain this is that we all know that humans are not efficient enough to process data and the complex patterns that appear within large datasets.

However, AI can easily do this job using sensor data of a manufacturing machine and pick out outliers in the data that provide information about the machine that will require maintenance in a few weeks. Artificial Intelligence can perform this in a fraction of a human’s time analyzing the data.

Robotics: The foundation of Modern Manufacturing

Many applications of artificial intelligence include software in place of hardware. However, robotics is mainly focused on highly specialized hardware. As per Global Market Insights, Inc, the industrial robotics market is expected to grow more than $80 billion by 2024. In many factories, for instance, Japan’s Fanuc Plant, the robot-to-human ratio is approx 14:1. This reflects that its possible to automate a large part of the factory to reduce product cost, improve human safety and enhance efficiency.

Industrial robotics demands specific hardware and artificial intelligence software to assist the robot in accurately performing its tasks. These machines are specialized and are not in the business of making decisions. They can run under the supervision of technicians, and if not even, they make very few mistakes compared to humans. Since they make very few mistakes, the overall efficiency of a factory improves when integrated with robotics.

When artificial intelligence is integrated with industrial robotics, machines can automate tasks like material handling, assembly, and inspection.

Robotic Processing Automation:

Robotic processing automation, artificial intelligence, and robotics are among the most familiar. It is important to understand that this process is not related to hardware machinery but software.

It involves the principles of assembly line robots for software applications like data extraction, file migration, form completion and processing, and more. However, these tasks do not play very important roles in manufacturing; they are significant in inventory management and other business tasks. It becomes more important if the production operation requires software installations on each unit.

Computer Vision: AI Powering Visual Inspection

Quality control is the manufacturing industry’s most significant use case for artificial intelligence. Even industrial robots can make a mistake, though the possibility is less than humans. It can be a huge loss if a defective product reaches the consumer by mistake. Humans can manually monitor assembly lines and identify defective products, but no matter how attentive they stay, some defective products will always slip through the cracks. Therefore artificial intelligence can help the manufacturing process by reviewing products for us.

Adding hardware like cameras and IoT sensors, products can be interpreted by AI software to catch defects automatically. The computer can then automatically decide what to do with defective products.

Natural Language Processing: Improving Issue Report Efficiency

Chatbots driven by natural language processing is an important manufacturing AI trend that makes factory issue reporting and helps requests more efficiently. It is a domain of AI that specializes in mimicking natural human conversation. Suppose workers can access the devices to communicate and report their issues and questions to chatbots. In that case, artificial intelligence can support them in filing proficient reports more promptly in an easy-to-interpret format. It makes workers more accountable and decreases the load for both workers and supervisors.

Web Scraping:

Manufacturers can use NLP for an improved understanding of data collected with the help of a task called web scraping. AI can check online sources for appropriate industry benchmark information and transportation, labor, and fuel costs. It can help in boosting business operations.

Emotional Mapping:

Machines are quite poor when it comes to emotional communication. It is very challenging for a computer to understand the context of a user’s emotional inflection. However, natural language processing is enhancing this area through emotional mapping. This brings a wide variety of opportunities for computers to understand the feelings of customers and operators.

Machine Learning, Neural Networks, and Deep Learning

The three technologies used in the manufacturing industry are machine learning, neural networks, and deep learning, which are artificial intelligence techniques used for different solutions:

Machine Learning: It is an artificial intelligence technique in which an algorithm learns from training data to decide and identify patterns in collected real-world data.
Neural Networks: Using ‘artificial neurons,’ neural networks accept input in an input layer. The input is passed to hidden layers that increase the weight of the input and direction to the output layer.
Deep Learning: It is a machine learning method where the software mimics the human brain like a neural network, but the information goes from one layer to the next for higher processing.

Future of AI in Manufacturing

What will be the next role of artificial intelligence in manufacturing? There are so many thoughts and visions coming from science and technology. The most visible change will be an increased focus on data collection. AI technologies and techniques used in manufacturing can do so much work independently. As the Industrial Internet of Things grows with increased use and effectiveness, more data can be gathered and then used by AI platforms to improve different tasks in manufacturing.

However, with the advancement in AI in the coming years, we may observe completely automated factories and product designs made automatically with less human interference. However, reaching this point is only possible through continuous innovation. All it requires is an idea- it can be the unification of technologies or using technology in a new case. Those innovations alter the manufacturing market landscape and help businesses stand out.

Energy Harvesting and IIoT- Sustainability for the IIoT

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September 19, 2022

Energy Harvesting and IIoT: Sustainability for the Industrial IoT

The world is encountering tremendous economic and ecological changes along with challenges. The futuristic technologies are all set to transform the outlook of Internet of Things (IoT). Today energy supply to millions of communicating devices is a key issue.

On a large scale, renewable energies have become a major source of energy generation. Fields embracing solar cells that generate energy using sunlight or wind turbines dominate the landscape. This renewable energy for energy generation is also embraced on a small scale. This entire concept is called “energy harvesting.”

Small energy converters harvest energy from light, movement, or temperature differences. These harvested energies are enough to power a wireless sensor and transmit data using radio.

Energy harvesting for radio-based products that are already part of mass production includes four different sources:

Motion – the press on a switch, moving machine parts, the rotary motion of a handle.
Light– the sunlight coming inside a room.
Temperature differences – existing between a heat source like a boiler, radiator, or pipes and the environment and variation between day and night.
Electromagnetic field – a contactless coil in a cage clamp around a cable controls the meter and calculates the line current.

For each source, different energy converters with different power parameters are present. The energy generation type and the corresponding power yield determine the possible sensor applications.

Enhanced Sustainability:

With the introduction of energy harvesting technology, radio sensors are sustainable as they don’t require cabling or battery power. They are environment friendly as well as cut expenditure.

Replacing a single battery typically costs around $300 US dollars in an industrial environment. Though changing the battery does not consume much time, traveling to the site, locating the sensor, testing the device, and documenting the process increases the labor cost. It is believed that batteries have a good service life, but in reality, companies are often engaged in changing them within one or two years to avoid early failures.

Today, resource-saving and environmental protection are the top priority. The rising cost of copper, the presence of harmful components, and battery safety are some serious issues. Wireless energy harvesting sensors are the best solution that considers both the financial aspect and environmental protection.

In Process for The Industry:

Sensors play a key role in industrial production. They can be used for quality and process monitoring or condition-based maintenance. A wide range of applications is developing in the direction of an industrial Internet of Things (IIoT) with the increasing usage of wireless sensors. Integrating energy-saving radio with local energy converters,battery-free and maintenance-free sensors can be installed directly on moving parts or in hermetically-sealed environments. For instance, it can be implanted to know the position of moving parts, power consumption, temperature of moving parts, liquids, or gases.

Sensors in Quality Control:

Quality monitoring manages the entire production process and ensures the desired properties of the end product based on different parameters.

For this purpose, environmental factors like temperature, humidity, and air quality or process factors like position or temperature are monitored.

Automated monitoring systems require data generated by sensors; for this purpose, sensors must fit seamlessly into existing production processes. Additionally, they must not need special training or generate follow-up costs in the ongoing operation. Therefore the integration of self-powered and maintenance-free sensors provides benefits.

Condition-based Maintenance with Battery-free Sensors:

Besides products, machines also need proper monitoring to ensure a seamless production process. These are prone to high wear, so it would be best to identify problems as soon as possible and take appropriate actions to maintain continuous quality assurance and protection against production downtime.

A primary problem with maintenance planning is the calculation of the intervals between each maintenance cycle. Normally, the interval between two maintenance dates must be as short as possible to detect deviations before any mishappening occurs. Still, each maintenance involves high costs for personnel and idle machines.

It is often possible to derive valuable information by closely examining a few simple parameters. For instance, a temperature rise can indicate higher friction, thus resulting into wear. Wireless temperature sensors can be installed for measurement processes. Humidity sensors monitor water leakage to prevent water damage. Temperature and humidity sensors also inform about air conditions and guarantee good air quality. That is why wireless energy harvesting sensors are best for various industrial applications. They are low maintenance, flexible, and within budget to install.

That is why wireless energy harvesting sensors are ideal for various industrial applications. They are maintenance-free, flexible, and inexpensive to install – outstanding features for assuring high-quality standards and greater sustainability in the Industry 4.0 environment.

IoT in the Factory Building:

IoT allows significantly efficient, adaptable, and individualized production in manufacturing. Using sensors networked with a smart IoT platform, it is now possible to develop a digital twin, i.e., an exact virtual image of a machine throughout its entire life cycle. Digitalization is becoming a part of buildings and will revolutionize them by providing automated service processes in facility management, higher energy savings, and better individual well-being for users. One important thing for factory buildings and industrial processes is battery-free wireless sensors.

Which solution is best for your Connected Device- Edge or Cloud Computing_

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September 5, 2022

Which Solution is Best for Your Connected Device – Edge or Cloud Computing?

If you have adopted IoT and are developing an IoT-connected device, you may wish to do some valuable computation to resolve the important issues that have been hindering growth. You might be desiring to install sensors in remote locations, create a device that can do data analytics to watch a renewable energy source, or develop health-related devices that can detect the early signs of diseases.

While creating the IoT-enabled device or IoT solution, at some point, you might get into a dilemma where you have to choose between edge or cloud computation. But what would be best for your device? Where should your device do the valuable computations in the cloud or at the edge?

Selecting between computing on edge or cloud can be an impacting decision, like it can influence a device’s efficiency or cost. Therefore, everyone does great research and thinks twice to avoid the cost of making the wrong decision and then the money spent correcting it.

What is Cloud Computing?

Cloud- It is a collection of servers accessed over the internet. Some renowned cloud providers are Microsoft Azure, Amazon Web Services, and Google Cloud.

These servers offer on-demand computing resources for data processing and storage purposes. You can easily say that cloud is a centralized platform for storing your files and programs, and you can easily connect any device to the cloud to access the data. Some of the cloud-based services are Dropbox or Google Drive etc.

Cloud computing is the process of doing computation in the cloud. These computations include data analysis and visualization, machine learning, and computer vision.

What is Edge Computing?

Edge is described as the “edge” of the network that includes devices at entry or exit points of the cloud, but it is not a part of the cloud. For instance, a server in a data center is part of the cloud; however, smartphones and routers that connect to that server are part of the edge.

Edge computing can be defined as the process of performing computations on edge. In this, the processing is completed closer or at the location where data is collected or acted.

One example of an edge computing process is object detection attached to an autonomous vehicle. The vehicle processes the data from its sensors and utilizes the result to avoid obstacles. In this process, the data is processed locally rather than sent to the cloud.

What are the points to be considered?

Before opting between edge and cloud computing, a few key questions must be considered.

Quality of Your Device’s Network

Conducting computation on the cloud can be beneficial if you have high bandwidth, low latency, and a sturdy connection to the internet, as you’ll have to send your data back and forth between cloud servers and your devices. If you have to use your device, for example, in an office or home with a steady internet connection, this back and forth can be done seamlessly. In most cases, if computation is conducted on edge, it won’t be affected by the bad or lost internet connection in a distant place. The processing can continue as it is not performed in the cloud. You would never want your vehicle’s objection detection to be failed while driving on the road. It is one of the reasons why autonomous vehicles perform computations like object detection on edge.

How Swift and How Often Does Your Data Need to be Processed?

Edge computing can be best suited in cases where customers demand response times from devices prompt than waiting for it in a decent network connection, such as monitoring components of the device.

The latency of the travel time between the cloud and the device can be minimized or eliminated. It means data can be processed immediately. It implies that if data processing is quick, one can achieve real-time responses from the devices. Cloud computation is also useful when device use is unsteady. For example, smart home devices running computation in the cloud allows sharing of the same computing resources between multiple customers. This decrease costs by restraining the need to provide the device with upgraded hardware to run the data processing.

What Part of Your Data is Crucial to You?

Computing on edge is helpful if you are only concerned about the result of your data after it has been processed. One can only send only important things for long-term storage in the cloud, which may cut down the expense of data storage and processing in the cloud. Suppose you are developing a traffic surveillance device that needs to inform about the congestion situation on the road. You could pre-process the videos on edge- instead of running hours of raw video in the cloud-one can send images or clips of the traffic only when it is present.

Do you know Your Devices’ Power and Size Limitations?

If you think your device will be limited in size and power, provided it has a strong network connection, sending the computing work to be done on the cloud will permit your device to remain small and low-power. For example, Amazon Alexa and Google Home capture the audio and send it to the cloud for processing, letting complex computations run on the audio as it can not run on the small computers inside the device themselves.

Data Processing Model Your Intellectual Property?

If you are creating a device for costumer and the methods you are adopting to process data are part of Intellectual Property, you must rethink the plan to protect it. Placing your IP on your device without a proper security plan can make your device vulnerable to hacks. If you are unaware of resources to secure your IP on edge, it is best to opt for the cloud, which already has security measures.

Final Reasons for Choosing Between Edge and Cloud Computing

Hence, we can conclude that one must consider a few things when choosing between computing on edge or the cloud. In complex issues, you might find the combination of both very beneficial by leaving some parts of processing on the cloud and rest on the edge.

admin

August 24, 2022

How will 5G Revolutionize the Healthcare Industry?

Today, we are advancing in terms of technologies, but using these latest technologies to their best, we need good internet connectivity. The journey from 2G to 4G has been incredible, and now we are switching to 5G and private networks. When 5G will dominate and cover most of the area in the coming years, what would be the possible changes in different industries?

Any idea?

Undoubtedly, 5G and private networks will hugely impact the future of the different sectors and industries, including healthcare.

Besides upgrading the wireless communication ecosystem, 5G will also enhance global innovation by integrating other latest technologies like edge computing or AI. The demand for more connectivity and data requirements will be addressed by 5G as it offers ultra-fast connections and gigantic bandwidth to boost companies’ efficiency and innovation skills.

Therefore, let us know how 5G will work and save lives by allowing faster response time, sharing patient information, and promising better data security.

Why do we need 5G in Healthcare?

Today, there are several issues faced by the connected healthcare solutions, like:

Data security issues because of wifi networks and legacy telecom technology.
Availability of Single-network SIMS and expensive roaming solutions.
Less accessibility to private 5G/LTE Networks.

Hence, 5G and private networks are most-demanded because of their capability to transfer data at much higher speeds while promising greater security. This will definitely offer countless possibilities within the healthcare ecosystem.

The top benefits of using 5G and private networks for healthcare include:

Reduced latency for more rapid communication between healthcare providers and patients.
Unmatched security to ensure that patient data stays secure (especially compared to wifi and Bluetooth alternatives).

Where is 5G Making an Influence?

5G is going to impact almost every sector, but five primary sectors that will be influenced by it are:

1: Wearables and Connected Medical Devices:

The wearables market is growing rapidly, and apparently, its adoption in Healthcare is the highest. These IoT-enabled smart devices support patients and healthcare providers monitor important biometric data and assure prompt emergency response time.

Some of the devices which are helping healthcare centers are:

Glucose monitoring devices
Cardiac monitoring devices
Fitness trackers
Smartwatches

2: Connected Emergency Services:

IoT-connected ambulances can be labeled as the future of emergency response. 5G empowers doctors and paramedics to cooperate in real-time even when they are at distant places. These smart ambulances offer more details about patients and their health history promptly than ever before; this plays a crucial role in changing how emergency services can be delivered.

3: Drone Delivery of Medical Supplies:

When the COVID-19 pandemic hit the world, paralyzing every section, drones were employed for remote virus testing and to deliver medical supplies. These drones were primarily used to support underserved societies worldwide, but 5G in Healthcare plays an important role in assuring these kinds of use cases stay connected in the future, particularly within cities.

4: Employee Panic Buttons:

Hospitals all over the world are taking advanced steps to ensure safety and peace within the campus. They are arming nurses with employee safety devices- “panic buttons” responding to news of hospital violence.

Three in ten nurses who participated in a survey conducted on violence within hospitals shared that there is an increase in violence cases at their hospitals. These cases are the result of staff shortages and strict visitor restrictions. Panic buttons must remain connected; both 5G and private networks within hospitals can ensure these devices stay functional as they greatly support employees’ safety.

5: Hospital and Medical Campuses:

Demand for 5G and private networks in Healthcare is increasing day by day. Private LTE/5G Networks has improved security features, and many hospitals and medical premises can use these private networks to assure data security and HIPAA compliance. Private 5G/LTE networks are usually deployed as a replacement for wifi, which lacks enhanced security for transferring health and personal data over the Internet.

5G will transform Healthcare from head to toe:

The intrusion of the COVID-19 pandemic made us realize the importance of the connected healthcare industry and showed us how the latest technologies could evolve healthcare. It also emphasized the importance of monitoring and treating patients from remote areas using virtual connections.

5G will surely revolutionize every aspect of healthcare, from wearables to emergency services, from supply chain optimization to remote diagnostics to electronic medical records management, from panic buttons to drones, hospitals, and medical campuses.

As per the report on 5G in Healthcare, PwC shared that it is not expecting extensive use until 2025 in many markets. When widespread deployment happens, PwC predicts 5G-compatible devices being utilized to monitor bed occupancy levels, the movement of physicians, nurses, and patients around the hospital premises, and wearable medical devices. So, we can conclude that by reducing latency, improving reliability, and boosting security, new healthcare use cases will benefit from the availability of 5G and private networks.

Skills and Apps Needed for IoT Mobile App Developers

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July 25, 2022

What are Skills and Apps Needed for IoT Mobile App Development?

Nowadays, it is quite apparent that most of the Internet of Things that is IoT solutions or services are dependent on mobile applications. If we look around, we’ll find that either for industrial or consumer or commercial use cases, mobile applications are important user interfaces to interact, configure and control connected devices or digital services in an IoT system.

Many traditional mobile application development companies share that they are ready to embrace IoT but add that creating IoT applications requires much effort and expertise.

Suppose a traditional app development includes IoT as just one of their mobile capabilities. In that case, it should be considered a warning flag because IoT requires knowledge and expertise, which comes with focusing on IoT over a long time.

What are Important Mobile App Skills for IoT Developers?

Bluetooth Low Energy:

Bluetooth Low Energy enables smartphones to connect directly to IoT devices like sensors, smart appliances, and others. This allows mobile apps to perform works like collecting data from the devices or controlling or configuring the behavior, provision network credentials and updating the device’s software, and many other things.

This BLE is based on the same radio technology as traditional Bluetooth but consumes less power. This feature makes BLE the best for battery-powered IoT applications that do not send or receive a large amount of data. BLE provides support for modern smartphones. It is especially useful in providing network credentials, like sharing wifi SSIDs and passwords to an IoT device. The important point is to do this securely, mandating know-how beyond the basics.

Besides this, working with BLE demands knowing the communication protocols and unique behaviors of the IoT devices. This implies knowing how to troubleshoot the problems and debug issues. Other than this, it also demands experience working with the embedded microcontroller systems that power most devices. The traditional mobile app firms often do not get this type of experience. Pertinent details of the nuances of BLE in different mobile application frameworks like React Native, iOS, and Android environment is also important. Every framework or environment works differently.

Zero-Configuration Networking:

Zero-configuration or Zeroconf is another way smartphones can detect and interact with nearby devices. This system is less used than BLE for this purpose but is often employed for communicating with devices connected to the smartphone’s local wifi network. There are different protocols available that permit the mobile app to discover devices present in the network without needing any special network configuration. Therefore, these protocols are altogether known as Zero-Configuration Networking. These protocols consist of MultiCast DNS (MDNS) and Apple Bonjour.

Smartphones transfer different messages on the network to detect specific device types. The devices supporting the protocol will react with their service name and IP address. This allows the smartphone to develop a direct connection with the device. It is important to have skills and experience with networking and embedded devices for implementing Zeroconf networking.

IoT Cloud Service Integration:

Most of the IoT mobile apps integrate with IoT cloud services. This integration to digital services operating in the cloud allows users to communicate with the devices even when they are not in the range. It also allows users to get useful insights from IoT system data.

Cloud service providers offer many software solutions for IoT systems that can do things like route messages, process events, index devices, and aggregate data. Mobile apps interact with these services.

Often, mobile apps for IoT communicate with custom cloud APIs to streamline the interaction between the cloud services and mobile applications. Having experience with REST API and HTTPS is important, and for IoT applications, knowing MQTT and GraphQL.

Executing good security protection is crucial when connecting to cloud services. To establish this, it needs expertise in methods for authenticating user accounts and setting up access protocols. The entire system ensures that the right users and systems access the right resources, not others. Establishing good security is not a small task and demands precise knowledge of the IoT system and its implementations. Therefore, mobile app developers holding loud experience, specifically IoT-oriented cloud services and patterns, are highly useful for developing great mobile apps for IoT. Holding a good connection with multiple cloud service providers and their capabilities and subtleties add a lot of worth. This also helps select the most optimal services and their providers for specific purposes.

Interfacing with IoT Devices:

IoT system connects the physical devices using networks to digital services and user interfaces. To perform the functions, physical devices have computing capabilities embedded inside them. These small compute consist of external interfaces to get sensor measurements, drive the display, store data, etc. We already discussed that mobile apps often connect to IoT devices over BLE, but the data shared over BLE varies by device type. The way data is collected and sent over BLE depends on the firmware operating in the device. The data available could be in any format, including binary. To exploit this data and debug any issues when they come up, it is important to know decoding, encoding, serialization, and bitwise operations.

Knowing how the IoT device works is important to understand the data needs. This may need reading datasheets and specification documents and reviewing the embedded firmware. Having information about embedded systems mobile makes this process seamless and more efficient.

Security:

IoT systems run on networks and manage important and private data. Therefore, they become the target of attacks from cyber criminals, security researchers, and others. Hence, IoT systems should have good security measures to safeguard the products and brands.

Authentication of users and devices is an important part. Mobile apps should ensure that users trying to log in are valid and even detect invalid users. Depending on the account, the user should have unique permissions and data access policies. Along with this, mobile apps also need to ensure that any device a user attempt to connect to is authentic and has not been tempered. This is only possible using cryptographically signed software and digital certificates. The data shared between devices and mobile apps should be encrypted. Mobile apps play an important role in updating the firmware of the specific connected devices they are developed to support. This requires securely downloading firmware files, verifying them, and transferring them over the device. To create such systems, it is important to have end-to-end security knowledge. Experience with data access policies and Over-the-Air firmware updates with cryptographically signed firmware is also important.

Cross Platform Development:

Well, there is no need to put effort twice and write two apps when you can have one? Earlier, there was a need to develop two separate applications for Android and iOS.

However, today there are cross-platform development frameworks that serve both. This implies that a single development project can offer mobile applications for both Android and iOS. It has been found that cross-platform development frameworks like React Native and Flutter can provide excellent results in minimum time. These frameworks permit developers to write code in a single language and render applications in native code. The native code varies between Android versus iOS. This means there is no difference in the performance. The final mobile apps perform well and provide the look and feel that Android or iOS users expect. These frameworks have been employed in thousands of web applications and mobile applications. Using a common framework for web and mobile applications adds many advantages to the consistency of user experience.

Mobile App Architecture for IoT:

Mobile apps for IoT should look great and operate flawlessly. The best people to develop the user interfaces must necessarily be the developers with a good grip on core functionality.

Suppose a company delivers the core IoT capabilities for an app inside a bundle of software that partner companies or customers can use within the mobile application. This enables them to focus on developing a seamless user experience without considering the complexities of the IoT features underneath. Your developer should pack the core IoT capabilities into mobile software development kits that can summarize all the IoT complexity into a compilation of software that reveals clear APIs to other mobile app developers.

These SDKs, i.e., software development kits, have APIs for cloud connectivity, device data access, account management, etc. This allows mobile developers to have less IoT complexities experience and access to the IoT APIs to prioritize the application’s user-facing features.

Summary

These are a few reasons advocating Mobile Apps for IoT are unique and require unique skills to develop. These consist of IoT-specific mobile app development features like BLE and the cross-domain experience like cloud and embedded.

If you wish to add great IoT experiences for customers, collaborate with a company with a forte in IoT development and implementation. Connecting with an experienced mobile app development company can improve your business and provide a greater user experience. IoT is the next-gen technology with the only objective of simplifying the existing complex system. It also ensures that customers don’t struggle while using apps or services, and on the other hand, it saves time and cost for the service providers.

How will IoT Build a Bright World with Connected Devices

admin

July 11, 2022

How will IoT Build a Bright World with Connected Devices?

Internet of Things is now no new word for the tech world. Studies show that the number of connected devices will reach more than 75 billion by 2025, implying that there will be possibly nine connected devices for every human on earth.

The pace at which IoT technology is striking every area of our lives is impressive, but how it has transformed our day-to-day work is beyond imagination.

But what is IoT?

In simple words, it is the practice of connecting different physical assets through the internet, providing control and measurement access from the remote area while saving users money and time. Today one can set the temperature of the air conditioner while on the way home, brew coffee and efficiently manage the use of lights in the home. Products like Amazon’s Alexa and Apple’s Siri can interact and provide information as required.

Let us know how various industries are embracing the presence of the Internet of Things and the impact of this latest technology.

IoT in the manufacturing sector:

The impact of Industrial IoT technology is already visible in the output of the manufacturing industry, especially in measuring energy and asset efficiency throughout the production line.

IoT technology has provided an effective way to connect and modernize legacy assets. Using connective sensors, businesses can accumulate critical production data and use cloud software to turn this data into useful insights to know about the efficiency of their manufacturing process. But what kind of assets? It can be anything used within the manufacturing process, from its HVAC or CNC machines to products like refrigerators or lighting rings, etc.

IoT can assist by providing a clearer picture of the working of assets individually and collectively, chartering better ways for monitoring, automation, and predictive maintenance. For instance, Industrial IoT in action has enabled us to gain insight into energy consumption and the health condition of the asset. This technology even allows us to schedule maintenance by informing us about the future condition of the asset.

Employing and integrating IoT in the existing process reduces costly downtime, improves assets, and reduces energy costs.

IoT in the retail sector:

Retail sectors are already using IoT in different innovative ways. One of the key areas is tracking energy consumption not at one store but all the stores present in the entire region or at the national level.

The IoT system can also be used to know which stores are using high energy in lighting or heating; in-store sensors allow us to track energy usage at a more granular level.

Other than this, IoT is also used to optimize store experiences. It is now possible to know the interest area of the shoppers, where they are spending most of the time. This helps retailers improve their stores’ layout to reduce congestion, increase stay time and boost sales. We can say that IoT technology and its different uses are building the ‘high streets of the future.

IoT in the construction sector:

Internet of Things is also contributing to making the construction sector smarter. Smart buildings are one of the most loved concepts possible by IoT. Using IoT and integrated sensors to know the air quality of the site or the surrounding area, such as parks and schools, is one of the key usages.

IoT in construction areas allows construction managers to accurately assess the real-time effect of their work on air quality. IoT in construction also ensures the safety of construction workers and nearby people.

IoT in the agriculture Sector:

The increasing population shows that we will need more food production in the coming year. UN has also estimated that we will need to produce 70% more food to meet the global demand by 2050. Internet of Things will help this sector overcome the looming food shortage challenge by reducing food wastage and increasing yield.

Supervising and tracking workers, machine efficiency, crop and livestock health, and predicting weather are some of the ways through which IoT promises to boost productivity with minimum wastage. Employment of agriculture drones and smart agriculture sensors are already helping agriculture workers by providing real-time production data. Besides this, sensors to track important atmospheric aspects like light, humidity, temperature, air quality, and soil aspects like soil moisture, nutrition, etc., contribute to better yield. This has automated the tasks which involved manual and human interference. Thus, saving labor costs and time as well.

Another way through which IoT is helping agriculture farmers is by providing predictive analytics through better quality data. Using data, farmers can estimate the yield and make better storage plans to keep the produce after harvesting.

IoT in smart cities:

Well, IoT in urban areas has been very influential. People are enjoying the leverages provided by IoT like smart houses, smart street lights, or smart bottles. IoT has occupied an important place in the planning and management of cities. Many countries are using IoT for waste management, traffic control, and public transport systems.

Using IoT, it is now possible to know the number of people in transit at a particular time and opt for a better route to avoid congestion. In cities where flooding is a serious concern, IoT can be used to track the real-time water level in the river. The flood defense system starts when the water level increases and helps mitigate the risk.

We’re on the way to a smart connected world:

IoT has successfully infiltered in major sectors contributing to the economy’s growth. Today, if we look around, we’ll observe that everything is getting smart and automated. All thanks go to IoT for making life more hassle-free and productive. However, some areas are still untouched by the magic of IoT, but it is predicted that it will be covered soon in the coming years. It is estimated that global expenditure on IoT will be around $1,100 billion (€1060.02 billion) in 2023, almost double 2018 $646 billion (€622.52 billion).

This shows that IoT will continue to reform the industries making them more profit-oriented without compromising quality. Hence, we can conclude that high-quality data can help make anything prompt, cheap, and more efficient with less waste.

admin

June 27, 2022

How To Build Smarter Apps Using Mobile Artificial Intelligence?

Mobile artificial intelligence is already revolutionizing the mobile app development game. In 2020, the mobile AI sector crossed the valuation of 2.14 billion dollars, and this number will possibly grow 4.5x by the year 2026. It is quite apparent that mobile artificial intelligence holds a great future so let’s not waste time and know this innovative technology and its use in mobile app development.

What are the benefits offered by Mobile Artificial Intelligence?

Mobile artificial intelligence endeavors to make mobile technology smarter and more functional for users. Amazon’s Alexa Shopping product is a very popular example of mobile Artificial Intelligence. It has reduced countless hours of customer support work for Amazon. At the UX level, it has also brought prominent quality of life improvements to end-users.

It is expected that the most significant growth will likely come from AI virtual assistant technology. The remarkable success of last-generation AI assistants like Alexa and Siri shows the power of the technology.

AI-capable processors in next-gen mobile devices are featured with various intelligent solutions such as language translators, AR and VR enhancement, context-aware AI assistants, and better security attributes.

The fortune of these advanced apps and on-board solutions is highly extensible, and its integration with the third-party mobile application provides developers with a full-fledged AI development ecosystem.

It is also projected that sectors such as smartphones, cameras and imaging, drones, robotics, automotive, and cloud computing also show incredible growth from mobile AI technology.

The government of the United States and other western countries are trying to prohibit restrictions on consumer drone technology; the drone sector will expand steadily in the presence of AI-capable mobile processors.

Next-gen drones offer an amazing home, and enterprise user features like AI-assisted photography, surface mapping, GPS, AI autopilot and navigation, and many more applications.

Eventually, it is impossible to ignore the potential of next-gen AI to reduce numerous human hours using the AI app development pipeline. AI aids programmers in crushing barriers that consume a lot of time and money in processes like porting software across platforms and removing manual error-checking and troubleshooting once done by human testers.

How AI Makes Your App Smarter?

The increasing number of mobile users and change in trend is shifting the demand toward more customized features.

Earlier, UI was managed in a first-party way by app developers; now, many app developers use on-board UI from smartphone manufacturers to offer an interface for their users. These manufacturers include AI-capable processors, smartphones can interpret user behavior and conduct real-time customization of the app interfaces for a better user experience.

Thus we can say that Artificial intelligence fetches remarkable new possibilities for mobile development via machine learning, biometrics, recognition technologies, and voice technologies.

Machine Learning:

Today, many businesses are investing so much money into machine learning development as it can predict and optimize user behavior, leading to upsells and cross-sells.

Machine learning improves a better user experience and ensures users keep returning by delivering appropriate content to drive up total usage hours.

The advanced technology has stirred up the competition in the app market. Machine Learning helps companies keep users engaged and entertained, ultimately improving their rank and rating on google play and other App stores.

Online retailers use ML to create customer profiles based on various data like customer purchases and their relationship with other users, the customer’s behavior on the app or website, and many other contributing factors. Using the data, retailers offer recommended products based on the customer’s interest.

For example, Amazon extensively uses machine learning to connect customers with products they might be interested in buying.

Transport providers like Uber also use this latest technology in their logistics apps to provide drivers with updated information on the road.

ML solutions predict the fasted possible route for drivers to avoid traffic jams.

Recognition Technology:

The addition of recognition supported by Mobile AI has changed the outlook of the entire mobile utilization pattern. Image recognition technology like Google Lens and other similar apps have revolutionized the way of interaction between people and the world. This image recognition app allows users to recognize the specific plant varieties, and OCR powered by ML can change the foreign language into the native language without delay.

Financial institutions are adopting the same technology in their mobile apps to process checks without needing the customer to visit the bank for the same purpose. Pharmacists are employing this tech to scan medical prescriptions and import them into software to know the exact place of the medicine or its availability in the store.

Next-gen mobile AI improves the existing facial recognition technology by using technologies like artificial neural networks to boost the process of detecting human faces.

AI biometrics boost the level of protection of mobile applications ensuring better privacy for storing sensitive data. This feature also increases the use of mobile applications in the sectors like finance, healthcare, government, etc.

Voice Technologies:

Highly advanced text-to-speech technology provided by mobile artificial intelligence provides clear voice functionality generated from text input. Better text-to-speech empowers visually impaired users to navigate apps and websites, changing static text into clear and understandable voiced content.

AI assistant technology uses voice recognition provided by mobile artificial intelligence to converse with the user without any latency. Commands by the users are processed into actions by the virtual assistant, offering a smooth experience.

For instance, our very popular Alexa and Siri of Amazon and Apple, respectively, can execute different user requests.

The Future Transformations

Mobile artificial intelligence is holding a great scope in the coming years. Many industries are embracing technology and facing rapid transition. Integrating mobile processors with AI- friendly features will enhance the AI capabilities of first and third-party applications.

The key technologies contributing to the changes are machine learning, recognition technology, biometrics, and voice technologies. Mobile AI optimizes the process, removes obstacles for users and providers, delivers relevant content, enhances end-user engagement, and improves the development process. AI-integrated mobile apps are more extensible, modular, dynamic, and offer superior performance for developers and users.

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