How To Use Machine Learning For Anomaly Detection And Condition Monitoring

Anomaly detection is the identification of the points, events items that are not expected to happen in the process. Anomaly detection is used for various domains such as fault detection, intrusion detection, and intrusion detection. The global anomaly detection market is increasing due to proliferation of black box trading by market traders.

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Anomaly Detection

Some of the key players influencing the anomaly detection market are Anodot, Ltd., Cisco Systems, Inc., Guardian Analytics, Happiest Minds, Hewlett Packard Enterprise Company, IBM Corporation, SAS Institute Inc., Symantec Corporation, Trustwave Holdings, Inc., and Wipro Limited among others.

Various vendors are focusing on providing innovative product integrated with enhanced technologies like artificial intelligence and business intelligence with the aim of gaining more customer. Increasing use of anomaly detection for software testing, and growth in the amounts of data are the major factors that are expected to drive the growth of anomaly detection market, whereas lack of skills is the major factor that impedes the growth of this market.

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The “Global Anomaly Detection Market Analysis to 2027” is a specialized and in-depth study of the anomaly detection industry with a focus on the global market trend. The report aims to provide an overview of the global anomaly detection market with detailed market segmentation by component, technology, deployment type, industry and geography. The global anomaly detection market is expected to witness high growth during the forecast period. The report provides key statistics on the market status of the leading market players and offers key trends and opportunities in the anomaly detection market.

Source:- The Insight Partners

How Image Recognition Will Transform Technology Industry

The image recognition market is experiencing high growth owing to increasing demand for security as well as the availability of image recognition technology powered products. Further, rising internet penetration coupled with high acceptance of social media is propelling the image recognition market growth. Moreover, the rising inclination of diverse industry verticals towards high bandwidth data services as well as machine learning has resulted in the bolstering the demand for image recognition market. However, high installation cost may hamper the image recognition market growth to a certain extent.

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Image Recognition

Some of the key players influencing the Image Recognition market are Google Inc., NEC Corporation, LTU Technologies, Hitachi, Ltd., Honeywell International Inc., Qualcomm Incorporated., Catchoom Technologies S.L.,Wikitude GmbH, Slyce Inc., and Attrasoft, Inc. among others.

The report aims to provide an overview of the global Image Recognition market with detailed market segmentation by component, technology, application, industry and geography. The global image recognition market is expected to witness high growth during the forecast period. The report includes key statistics on the market status of the leading market players and offers key trends and opportunities in the market. On the basis of the component the market is segmented as software, hardware, and services. On the basis of application the market is divided into identity management, law enforcement, border security, others.

The Image Recognition market research report offers a detailed overview of the industry including both qualitative and quantitative information. It also provides market size and forecast till 2027 for overall Image Recognition market with respect to five major regions, namely; North America, Europe, Asia-Pacific (APAC), Middle East and Africa (MEA) and South America (SAM). The market by each region is later sub-segmented by respective countries and segments. The report covers the analysis and forecast of 16 countries globally along with the current trend and opportunities prevailing in the region.

Source: The Insight Partners

How Has Deep Learning Impacted the Translation Industry?

Deep Learning

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Deep learning is a subset of advanced machine learning which uses artificial neural networks. The Asia Pacific region is utilizing deep learning not only in electronics but also across medical and automotive industry. The focus of major market players has been in adopting new product developments, product launches, partnerships, and collaboration as key strategies for market growth.

The deep learning market is anticipated to grow in the forecast period owing to driving factors such as growing usage of deep learning in big data analytics along with rapid adoption of cloud-based technology. Moreover, increasing focus on Artificial Intelligence in customer-oriented services is expected to boost the market growth. However, lack of standards and protocols may hamper the growth of the deep learning market during the forecast period. On the other hand, limited structured data is likely to create demand for deep learning solutions in the coming years.

The global deep learning market is segmented on the basis of component, application, and industry vertical. Based on component, the market is segmented as hardware, software, and services. On the basis of the application, the market is segmented as signal recognition, image recognition, data mining, and others. The market on the basis of the industry vertical is classified as automotive, manufacturing, healthcare, BFSI, and others.

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Some of the leading players in global deep learning industry are Amazon, Google, IBM, Intel, Microsoft, NVIDIA, QUALCOMM, Samsung, Sensory, Xilinx

Deep Learning definition aside, the potential for the deep neural network to crack machine translation is clear. The issues with machine translation have traditionally been around the poor quality of its results in terms of word choice, grammar, and sentence structure. Essentially, machine translation software delivers language that doesn’t sound natural, despite being fed tens of thousands (if not more) examples of written language.

Neural machine translation, which replaced the use of statistical machine translation back in 2015 and marked a significant leap forward, as a result, is therefore incredibly exciting. However, it still requires the machine to be fed comparable sentences in each of the languages it learns in order to translate them.

Source: The Insight Partners

How Connected Agriculture Is Changing the Way Farmers To Grow Food?

Connected Agriculture

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Connected agriculture assists the farmers on the tactics to use different methods, tools, pesticides, fertilizer, machinery, and other equipment increase productivity. Use of connected agriculture in farming activities also supports the farmers to increase their income level. With an aim to improve the level of farm yield while reducing labor wages is driving the connected agriculture market in a current scenario.

Some of the key players influencing the connected agriculture market are Accenture Plc, Ag Leader Technology, Decisive Farming, Epicor Software Corporation, IBM Corporation, Link Labs, Microsoft Corporation, Orange Business Services, Trimble Inc., and Vodafone Group Plc among others.

Key Benefits –

-To provide detailed information regarding the major factors (drivers, restraints, opportunities, challenges, and trends) influencing the growth of the global connected agriculture Market
-To forecast the size of the market segments with respect to four major regional segments, namely, North America, Europe, Asia Pacific, and the Rest of the World (Latin America and the Middle East & Africa).

However, due to limited awareness of connected agriculture technology introduced by IT industries for farmers, is one of a restraining factor responsible for creating barriers in the growth of connected agriculture market. Nevertheless, use of the internet for rural development including agriculture is expected to result in a prominent increase in social and economic benefits for the rural people which would nurture the connected agriculture market in the forthcoming period.

The report provides a detailed overview of the industry including both qualitative and quantitative information. It provides overview and forecast of the global connected agriculture market based on component, solution, application, and platform. It also provides market size and forecast till 2027 for overall connected agriculture market with respect to five major regions, namely; North America, Europe, Asia-Pacific (APAC), Middle East and Africa (MEA) and South America (SAM). The market by each region is later sub-segmented by respective countries and segments. The report covers analysis and forecast of 18 countries globally along with current trend and opportunities prevailing in the region.

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The "Global connected agriculture market Analysis to 2027" is a specialized and in-depth study of the connected agriculture industry with a focus on the global market trend. The report aims to provide an overview of global connected agriculture market with detailed market segmentation on the basis of component, solution, application, platform, and geography. The global connected agriculture market is expected to witness high growth during the forecast period. The report provides key statistics on the market status of the leading connected agriculture market players and offers key trends and opportunities in the market.

Source:- The Insight Partners

How is IoT Transforming Irrigation And Improving Agriculture !

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IoT has influenced various industry verticals and is enabling farmers to reduce waste and enhance productivity by using smart agriculture techniques. IoT in agriculture allows the farmers to monitor their crops using various types of sensor. The IoT in the agriculture market is highly influenced by increasing adoption of IoT and Ai solutions by farmers, and government support to adopt modern agriculture techniques. 

Some Of The Leading Players In Global IoT In Agriculture Market: Accenture, Climate Corporation, Deepfield Robotics, Farmers Edge Inc., Flux Farm, Inc., IBM Corporation, KaaIoT Technologies, LLC, Libelium Comunicaciones Distribuidas S.L, Octonion SA, Telit

Growing demand for agriculture due to increasing popularity, growing focus towards improving the efficiency and monitoring the crops, and supporting government norms are the significant factors that are expected to drive the growth of IoT in the agriculture market. However, high costs of solution and limited technical knowledge are the major restraining factors for IoT in the agriculture market. Increasing connectivity, the introduction of big data in agriculture are creating opportunities for the companies operating in the IoT in the agriculture market to gain a strong customer base and generate more revenues.

The global IoT in agriculture market is segmented on the basis of offering, application, and end-user. Based on offering, the market is segmented as automation and control systems, sensing and monitoring devices, livestock monitoring solutions, software solutions, and others. On the basis of the application the market is segmented as precision farming, livestock monitoring, aquaculture, and others. Based on the end-user the market is segmented into individuals and commercial.

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The "Global IoT in Agriculture Market Analysis to 2027" is a specialized and in-depth study of the IoT in agriculture industry with a special focus on the global market trend analysis. The report aims to provide an overview of IoT in agriculture market with detailed market segmentation by offering, application, end-user and geography. The global IoT in agriculture market is expected to witness high growth during the forecast period. The report provides key statistics on the market status of the leading IoT in agriculture market players and offers key trends and opportunities in the IoT in agriculture market.

Source: The Insight Partners

Artificial Intelligence is The Future For Cyber Security

AI in Cyber Security

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The cyber-attacks among organizations are getting more severe and complex, affecting their data as well as resource. Artificial intelligence in cybersecurity is a solution towards staying ahead of the threats and secure resources. Artificial intelligence can not only help in automated threat detection but also combat them without involving the workforce. The technology helps in securing sensitive data from malware and virus attacks across various sectors such as banking, financial services and insurance, defense, healthcare, manufacturing, government bodies and others.

Some of the leading players in global AI in Cyber Security market are Amazon, Cylance Inc., Darktrace, IBM Corporation, Intel Corporation, Micron Technology, Inc., NVIDIA Corporation, Samsung, Vectra AI, Inc., Xilinx Inc.

The market for artificial intelligence in cyber security is expected to grow in the forecast period on account of rising instances of cyber-attacks with increasing adoption of IoT and networking across all major industries. Moreover, concerns for data protection and vulnerability to threats over wi-fi connections is further expected to boost the growth of artificial intelligence in cyber security market. However, insider cyber threats and inability to avoid advanced threats pose quite a hindrance for the artificial intelligence in cyber security market. On the other hand, the requirements of security among SMEs is likely to offer lucrative opportunities for artificial intelligence in cyber security market.

The global artificial intelligence in cyber security market is segmented on the basis of components, deployment model, security type and industry vertical. By component, the market is classified as hardware, software and services. Based on deployment model, the market is segmented as cloud-based and on-premises. On the basis of the security type, the market is segmented as network security, endpoint security, application security and cloud security. The market on the basis of the industry vertical, is classified as BFSI, government & defense, enterprise, infrastructure, manufacturing, automotive & transportation, healthcare and others.

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The "Global Artificial Intelligence In Cyber Security Market Analysis to 2027" is a specialized and in-depth study of the technology, media and telecommunications industry with a special focus on the global market trend analysis. The report aims to provide an overview of artificial intelligence in cyber security market with detailed market segmentation by components, deployment model, security type, industry vertical and geography. The global artificial intelligence in cyber security market is expected to witness high growth during the forecast period. The report provides key statistics on the market status of the leading artificial intelligence in cyber security market players and offers key trends and opportunities in the market.

Source: The Insight Partners

Can Artificial Intelligence Help To Improve Agricultural Productivity?

Artificial Intelligence In Agriculture

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AI having applications in various sectors including agriculture has completely transformed the approaches of the agriculture market. AI in Agriculture helps the farmers in examining weather, soil, and field data to improve farming operations and crop productivity. AI in the agriculture market seems to be driven by the Internet of Things (IoT) due to its ability to revolutionize and transform current farming methods to a new level. Although, collecting accurate field data requires high initial investments which may hamper the growth of AI in the agriculture market.

Some of the key players influencing the market are Ag Leader Technology, Trimble Inc., Agribotix LLC, Granular, Inc., SAP, Mavrx Inc., PrecisionHawk, aWhere, IBM, and Prospera Technologies among others.

Key Benefits –

-To provide detailed information regarding the major factors (drivers, restraints, opportunities, challenges, and trends) influencing the growth of the global Artificial Intelligence in Agriculture Market
-To forecast the size of the market segments with respect to four major regional segments, namely, North America, Europe, Asia Pacific, and the Rest of the World (Latin America and the Middle East & Africa).

The report provides a detailed overview of the industry including both qualitative and quantitative information. It provides an overview and forecast of the global Artificial Intelligence in Agriculture based on by type, component, and application. It also provides market size and forecast till 2025 for overall Artificial Intelligence in Agriculture with respect to five major regions, namely; North America, Europe, Asia-Pacific (APAC), Middle East and Africa (MEA) and South America (SAM). The market by each region is later sub-segmented by respective countries and segments. The report covers analysis and forecast of 16 counties globally along with current trend and opportunities prevailing in the region.

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The “Global Artificial Intelligence in Agriculture Analysis to 2025” is a specialized and in-depth study of the Artificial Intelligence in Agriculture industry with a focus on the global market trend. The report aims to provide an overview of global Artificial Intelligence in Agriculture with detailed market segmentation by type, component, application, and geography. The global Artificial Intelligence in Agriculture is expected to witness high growth during the forecast period. The report provides key statistics on the market status of the leading market players and offers key trends and opportunities in the market.

Source:- The Insight Partners