Edge AI Software Market Expected To Reach USD 8,049.8 Million By 2027
NEW DELHI, 22 November 2021 / PRNewswire / – According to a study by Astute Analytica, we estimated that the global market for advanced AI software will see growth 29.8% CAGR during the forecast period 2021-2027.
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“The most demanding use of Edge AI has been seen in portable devices. “
Edge AI is a system composed of sophisticated machine learning algorithms that process data generated by a local hardware device. It is a system that combines Edge Computing and Artificial Intelligence (AI). AI is a machine designed to perform tasks that otherwise require human intelligence. Together, advanced computing and AI bring many revolutionary advancements such as self-driving cars, which help prevent many human-made accidents such as drunk driving or distractions. Since most self-driving cars have an electric motor, these cars have been proven to be environmentally friendly.
An application of cutting edge technology can be seen in the speakers of Google, Alexa or Apple Homepod, Apple Siri. These devices have comprehensive computer algorithms that help them learn and improve automatically using a large amount of data and given experiences.
In-depth study of the market and its effects
- Drivers: Growing demand for AI using devices
- The growing demand and trend for wearable devices such as smartwatches and smart glasses use advanced AI technology to provide real-time analysis and response. In 2021, Apple saw a 50% year-over-year increase in demand for its smartwatches.
- The need for futuristic security systems has grown rapidly. AI-enabled home cameras help detect activity with real-time facial recognition.
- Smart speakers and voice assistants integrated with cutting-edge artificial intelligence software provide a more interactive human interface.
- 5G coupled with Edge AI software aims to deliver a better customer experience, increase business efficiency, and generate higher revenue and more opportunities. For example, Telstra recently worked with Amazon Web Services (AWS) to combine AWS Edge AI technology with Telstra’s 5G network.
- Constraints: Continuing Cyber Threats
- Because Edge AI technology stores data in Edge devices, there is a large amount of real-time shared data that is prone to cyber theft.
- With the injection of AI with Edge Computing into the daily way of life of humans, the addiction is undeniable. Cyber attacks interfere with the proper functioning of technology.
- Internet of Things (IoT) devices are much more difficult to recover from security threats.
- Edge AI is used in banking bots, but with the rise of cyber threats it poses a scenario of bank failure. In addition, the interconnectivity of banks across the world also poses the plethora of cyber attacks simultaneously.
- Securing AI decision-making systems and creating public policies that create “AI security compliance” programs will reduce the risk of attacks against AI systems. For example, the NIST Cybersecurity Framework was developed to detect and protect economically important systems from AI attacks.
- Opportunities: Development of machine learning
- Adding machine learning (ML) to Edge AI software can improve IoT data analysis and decision making. The combination of machine learning and AI technology can filter noise collected by IoT devices and store important data only for analysis.
- In 2018, Google announced a few new products for ML and Edge Computing on the IoT, such as Edge TPU, which deploys a high-quality ML interface at the edge, and Cloud IoT Edge, which enables cloud data processing and learning. Google’s automatic to billions of Edge users.
- Trends: Use of Edge AI Technology in Healthcare
- With more precise and precise real-time data analysis, AI technology helps in the diagnosis and detection of various diseases.
- Neurological diseases weaken people’s ability to speak, move, interact and react. Brain-computer interfaces embedded in AI can help a person perform fundamental functions.
- Edge AI imaging tools can filter scans for the detection of various diseases with a level of precision even not performed by humans.
- One of the most emerging trends of the decade is the use of Edge AI in wearable devices. Some of these devices are fitness bands that track heart rate, number of steps taken, area covered while running, etc.
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Key players and recent developments
In recent years, the use of artificial intelligence has increased rapidly. Now more human tasks are done using AI technology to achieve increased efficiency at lower cost.
There are several players in the market that provide this technology extensively and the biggest vendors are AWS, Google, IBM, Microsoft, Azion technologies, Anagog Ltd., Foghorn Systems, Inc. Chaos Prime, Inc. Gorilla Technology Group, Inc Imagimob, Nutanix, Octonion, Synaptics, TIBCO Software, Veea Inc. The top 12 to 15 market players hold around 65 to 70% of the market share. The report assesses that the market is expected to evolve towards an oligopoly market during the forecast period. Some new developments in the global Edge AI software market are listed below:
- In 2019, Google launched Coral, an AI platform to help customers build products with local AI. Coral provides software-on-a-chip with machine learning algorithms that work without connecting to the cloud.
- In 2020, Mimik Technology collaborated with IBM to create integrated AI-enabled workflow technologies to make advanced computing more accessible for the manufacturing, retail, IoT industries. and health.
- In 2021, the National Payment Corporation of India (NPCI) has launched a sophisticated AI product called pai to integrate and analyze data from companies such as RuPay, FASTag, AEPS, etc.
- In 2021, Microsoft launched Azure Percept. The goal is to provide consumers with hardware and services that can facilitate the use of Azure Edge AI technologies.
- In 2021, Paravision released a toolkit integrated with Edge AI software that provides various facial recognition functions.
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Astute Analytica has segmented the Edge AI software market on the basis of component, data source, application, end user, and region:
In the component segment, the software category holds about four times the market share of the service category in 2020. In the data source segment, biometric data has the highest CAGR of 30.4%, closely followed by sensor data in second place. The advanced artificial intelligence software market is segmented on the basis of component, data source, application, end users, and region.
- Training and consultancy services
- System integration test
- Assistance and maintenance
By data source
- Biometric data
- Mobile data
- Sensor data
- Speech recognition
- Video and image recognition
- Access control
- Autonomous vehicles
- Energy management
- Predictive maintenance
- Remote monitoring
- Video surveillance
By end users
- Advanced industries
- Bank and insurance
- Chemical agriculture
- Vertical cross
- Energy and matter
- Healthcare infrastructure
- Media and entertainment
- Public sector utilities
- Travel, transport and logistics
- North America
- Western Europe
- Great Britain
- Rest of Western Europe
- Eastern Europe
- Rest of Eastern Europe
- Asia Pacific
- Australia & New Zealand
- Rest of Asia Pacific
- Middle East & Africa (AEM)
- United Arab Emirates
- Saudi Arabia
- South Africa
- Rest of the MEA
- South America
- Rest of South America
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SOURCE Clever Analytica