Tag: ABI Research

asset-visibility-market-opportunity-in-the-pharmaceutical-industry-worth-us$2.7-billion-by-2026

Asset Visibility Market Opportunity in the Pharmaceutical Industry Worth US$2.7 Billion by 2026

April 7, 2022 Published by

 

Pharmaceutical manufacturers, distributors, and transportation providers all face unique pain points within their supply chain operations. Product worth US$30 billion is damaged each year, and companies in the pharmaceutical space are concerned about how to control their spend on product, packaging, assets, and overhead costs, while also leveraging serialization and traceability throughout the broader supply chain. As a result, these enterprises are looking at asset visibility as a way not only to mitigate costs, but to use as a competitive advantage and to generate higher quality supply chain data both at an item level and at a network level. According to global technology intelligence firm ABI Research, these factors are creating an asset visibility market opportunity in the pharmaceutical industry worth US$2.7 billion by 2026.

“Supply chain visibility is increasingly becoming a priority for enterprises, and particularly so for those operating in the pharmaceutical industry who face a vast range of challenges, from meeting serialization and transport regulations to reducing product waste and damage,” explains Tancred Taylor, IoT Markets Research Analyst at ABI Research. “Enterprises need to adopt several different technologies to address these challenges, and technology suppliers specializing on one technology need to understand how to work with the rest of the ecosystem to become leaders in this market. IoT asset tracking will work alongside digital ID and telematics aggregation technologies to transform supply chain operations.”

Companies are approaching the challenge from many different directions. From an IoT perspective, Wiliot, Controlant, OnAsset Intelligence, Roambee, and Cloudleaf are examining how to digitize different types of assets to provide real-time tracking and monitoring capabilities. FourKites, Overhaul, Shippeo, TransVoyant, and numerous other fast-growing data aggregators are creating software-only approaches to bring visibility and analytics to shipment lanes and networks. Digital ID providers like Tracelink, rfxcel, or Kezzler are a third breed of technology suppliers enabling serialization and asset visibility in a complex supply chain which requires aggregation and disaggregation of products at multiple stages. Finally, packaging suppliers and pallet poolers are among those looking to capitalize on the greater perceived value of in-transit visibility data.

“The opportunity for asset visibility in the pharmaceutical supply chain is enormous. The ecosystem enabling this visibility and providing value-generating software on top is starting to work out how each tier of the value chain can collaborate with the others in what has up to now been a highly fragmented market. Technology suppliers need to adapt their strategies accordingly to ensure they can get a large share of the pie,” Taylor concludes.

These findings are from ABI Research’s IoT and Supply Chain Visibility in the Pharmaceutical Industry: Ecosystem Assessment application analysis report. This report is part of the company’s IoT Markets research service, which includes research, data, and ABI Insights. Based on extensive primary interviews, Application Analysis reports present in-depth analysis on key market trends and factors for a specific technology.

headline:-5g-and-network-data-analytics-function-(nwdaf)-to-fuel-growth-for-csps-in-the-digital-economy

Headline: 5G and Network Data Analytics Function (NWDAF) to Fuel Growth for CSPs in the Digital Economy

March 24, 2022 Published by

 

Data is the fuel that feeds algorithms and decision-making to drive growth in the digital economy. According to global technology intelligence firm ABI Research, data & analytics services revenue is expected to grow from US$140 million in 2021 to US$6.4 billion in 2026, at a CAGR of 115%.

“Data is becoming a crucial production element, data collection, storage, processing, and an understanding of the economic specifics of data are key strands that provide both challenges and opportunities. With data and analytics key to value creation, CSPs should adopt standards-based analytics functions to drive actionable insights in their operations,” states Don Alusha, Senior Analyst 5G Core & Edge Networks at ABI Research.

Network Data Analytics Function (NWDAF), for example, is an analytics function that provides operational intelligence, streaming, and data collection. Guavus and Sandvine are two vendors, among others, that offer full-featured and vendor-agnostic NWDAF capabilities that enable CSPs to place data and analytics at the heart of their innovation model. Also, NWDAF functionality is a stepping-stone for CSPs to build analytics functions that propel them forward in the digital economy. “In a digital economy where applications and APIs rule supreme, CSPs seek to become data-driven organizations. They should apply analytics at multiple ‘stations’ of the network spanning core, transport, and edge locations,” Alusha advises.

Orange, for example, claims that by the end of its Engage2025 strategic plan, most of its employees will have undergone Data and Artificial Intelligence (AI) awareness training. Every CSP will have a different foundation to build from and a different strategy. However, a common denominator among them is to leverage analytics functions, such as NWDAF, to change the structure of current systems and processes to produce more of what is desirable and less of that which is undesirable. There are challenges, particularly around best practices and obtaining the relevant human capital. But CSPs that rise to these challenges first may well gain a competitive advantage in the market.

CSPs do not seek a one-time attempt at innovation but rather sustainable productivity growth as a source of competitive advantage. With 5G, cloud, and big data analytics, the industry has the external catalysts that can drive new growth and innovation. But CSPs, and the broader industry, must realize that growth will come from combining and rearranging existing (cellular) technologies with big data and analytics solutions. New use cases need to be assessed on business impact and complexity in terms of skills required to deliver them. In addition to having the right tools and analytics functions (e.g., NWDAF), success for CSPs will come from how they use those tools. Orange, Telefonica, Vodafone, and Verizon are among the many CSPs investing to obtain the right know-how.

If CSPs are to be effective at using 5G big data and analytics, they should pursue a path that aligns with their unique circumstances. “It will not be so much about a 5G data platform and analytics as it will be about establishing the right operational context, for example, a fitting culture where everyone in the company seeks for ways for big data and analytics to enhance operations. At present, CSPs’ investments fall under two categories: one, buy out of the box models that improve execution and results of their product logic and operations; and two, buy analytics functions and big data models that have a positive impact on business results, for example, improve market share, improve revenue and sales, and explore new revenue streams,” Alusha concludes.

These findings are from ABI Research’s 5G Network Analytics and Network Data Analytics Function application analysis report. This report is part of the company’s 5G Core & Edge Networks research service, which includes research, data, and analyst insights. Based on extensive primary interviews, Application Analysis reports present in-depth analysis on key market trends and factors for a specific technology.

over-2-billion-devices-will-be-shipped-with-a-dedicated-chipset-for-ambient-sound-or-natural-language-processing-by-2026

Over 2 Billion Devices Will be Shipped with a Dedicated Chipset for Ambient Sound or Natural Language Processing By 2026

September 21, 2021 Published by

 

Natural Language Processing (NLP) and ambient sound processing are traditionally considered exclusive cloud technologies and this has restricted their adoption in markets where security, privacy, and service continuity are critical elements for deployment.  However, the advancements in deep learning compression technologies and edge Artificial Intelligence (AI) chipsets are now enabling these technologies to be integrated at the end-device level, which could mitigate security and privacy concerns while ensuring enabled services can be delivered consistently without interruption. ABI Research, a global tech market advisory firm, estimates over 2 billion end devices will be shipped with a dedicated chipset for ambient sound or natural language processing by 2026.

“NLP and ambient sound processing will follow the same cloud-to-edge evolutionary path as machine vision. Through efficient hardware and model compression technologies, this technology now requires fewer resources and can be fully embedded in end devices,” says Lian Jye Su, Principal Analyst, Artificial Intelligence and Machine Learning at ABI Research. “At the moment, most of the implementations focus on simple tasks, such as wake word detection, scene recognition, and voice biometrics. However, moving forward, AI-enabled devices will feature more complex audio and voice processing applications.”

The popularity of Alexa, Google Assistant, Siri, and various chatbots in the enterprise sector has led to the boom of the voice user interface. In June 2021, Apple announced that Siri would process certain requests and actions offline. Such implementation frees Siri from constant internet connectivity and significantly improves the iPhone user’s experience. ABI Research expects Apple’s competitors, especially Google, with its latest Tensor System-on-a-Chip (SoC), to follow suit and offer similar support on its Android operating systems currently supporting billions of consumer and connected devices .

In the enterprise sector, edge-based ambient sound processing remains in the nascent stage, with Infineon being one of the very early supplier of this technology. Increasingly, other sensor vendors are trialing the analysis of machine sound for uptime tracking, predictive maintenance, and machinery analytics. The combination of machine sound with other information, including temperature, pressure, and torque, can accurately predict the status of machine health and longevity.

Recognizing the importance of edge-based NLP and ambient sound processing, chipset vendors are actively forming partnerships to boost their capabilities. For example, Qualcomm has been working closely with prominent NLP startups, including Audio Analytics and Hugging Face. CEVA, a chipset IP vendor, announced a partnership with Fluent.ai to offer multilingual speech recognition technology in low-power audio devices. The recent collaboration between Synitiant and Renesas aims to provide a multimodal AI platform that combines deep learning-based visual and audio processing.

“Aside from dedicated hardware, machine learning developers are also looking to leverage various novel machine learning techniques such as multimodal learning and federated learning. Through multimodal learning, edge AI systems can become smarter and more secure if they combine insights from multiple data sources. With federated learning, end users can personalize voice AI in end devices, as edge AI can improve based on learning from their unique local environments,” concludes Su.

These findings are from ABI Research’s Deep Learning-Based Ambient Sound and Language Processing: Cloud to Edge application analysis report. This report is part of the company’s Artificial Intelligence and Machine Learning research service, which includes research, data, and analyst insights. Based on extensive primary interviews, Application Analysis reports present in-depth analysis on key market trends and factors for a specific technology.

over-2-billion-devices-will-be-shipped-with-a-dedicated-chipset-for-ambient-sound-or-natural-language-processing-by-2026

Over 2 Billion Devices Will be Shipped with a Dedicated Chipset for Ambient Sound or Natural Language Processing By 2026

September 21, 2021 Published by

 

Natural Language Processing (NLP) and ambient sound processing are traditionally considered exclusive cloud technologies and this has restricted their adoption in markets where security, privacy, and service continuity are critical elements for deployment.  However, the advancements in deep learning compression technologies and edge Artificial Intelligence (AI) chipsets are now enabling these technologies to be integrated at the end-device level, which could mitigate security and privacy concerns while ensuring enabled services can be delivered consistently without interruption. ABI Research, a global tech market advisory firm, estimates over 2 billion end devices will be shipped with a dedicated chipset for ambient sound or natural language processing by 2026.

“NLP and ambient sound processing will follow the same cloud-to-edge evolutionary path as machine vision. Through efficient hardware and model compression technologies, this technology now requires fewer resources and can be fully embedded in end devices,” says Lian Jye Su, Principal Analyst, Artificial Intelligence and Machine Learning at ABI Research. “At the moment, most of the implementations focus on simple tasks, such as wake word detection, scene recognition, and voice biometrics. However, moving forward, AI-enabled devices will feature more complex audio and voice processing applications.”

The popularity of Alexa, Google Assistant, Siri, and various chatbots in the enterprise sector has led to the boom of the voice user interface. In June 2021, Apple announced that Siri would process certain requests and actions offline. Such implementation frees Siri from constant internet connectivity and significantly improves the iPhone user’s experience. ABI Research expects Apple’s competitors, especially Google, with its latest Tensor System-on-a-Chip (SoC), to follow suit and offer similar support on its Android operating systems currently supporting billions of consumer and connected devices .

In the enterprise sector, edge-based ambient sound processing remains in the nascent stage, with Infineon being one of the very early supplier of this technology. Increasingly, other sensor vendors are trialing the analysis of machine sound for uptime tracking, predictive maintenance, and machinery analytics. The combination of machine sound with other information, including temperature, pressure, and torque, can accurately predict the status of machine health and longevity.

Recognizing the importance of edge-based NLP and ambient sound processing, chipset vendors are actively forming partnerships to boost their capabilities. For example, Qualcomm has been working closely with prominent NLP startups, including Audio Analytics and Hugging Face. CEVA, a chipset IP vendor, announced a partnership with Fluent.ai to offer multilingual speech recognition technology in low-power audio devices. The recent collaboration between Synitiant and Renesas aims to provide a multimodal AI platform that combines deep learning-based visual and audio processing.

“Aside from dedicated hardware, machine learning developers are also looking to leverage various novel machine learning techniques such as multimodal learning and federated learning. Through multimodal learning, edge AI systems can become smarter and more secure if they combine insights from multiple data sources. With federated learning, end users can personalize voice AI in end devices, as edge AI can improve based on learning from their unique local environments,” concludes Su.

These findings are from ABI Research’s Deep Learning-Based Ambient Sound and Language Processing: Cloud to Edge application analysis report. This report is part of the company’s Artificial Intelligence and Machine Learning research service, which includes research, data, and analyst insights. Based on extensive primary interviews, Application Analysis reports present in-depth analysis on key market trends and factors for a specific technology.

5g-smartphones,-smartphone-accessories,-and-vr-hmds-to-witness-high-growth-rates-in-2021

5G Smartphones, Smartphone Accessories, and VR HMDs to Witness High Growth Rates in 2021

June 4, 2021 Published by

 

According to the latest Consumer Technologies report from global tech market advisory firm, ABI Research, most consumer devices and services, especially 5G smartphones, accessories, and Virtual Reality (VR) Head Mounted Displays (HMDs), will remain healthy in terms of shipments in 2021 as the global economy recovers from the effects of the pandemic. Major players, including Apple, Qualcomm, Sony, and Amazon, will continue investing in the development of smart consumer products such as Augmented Reality (AR) smartglasses, smartphones, wearables, smart home devices, and consumer robotics to meet exacting consumer needs in a post- pandemic world. The resultant adoption of hybrid working, digital learning, at-home entertainment and telehealth, all indicate the need for improved intelligent devices and enhanced connectivity capabilities.

“True wireless headsets (TWS) are among the winning sectors in the smart accessories market, with many players, especially from the smartphone industry, launching TWS to remain competitive, while at the same time, expanding regionally and promoting a connected device ecosystem,” explains Eleftheria Kouri, Consumer Technologies Research Analyst at ABI Research.  Wireless headset shipments will reach over 1 billion units in 2025, with TWS accounting for 50% of sales, growing at a CAGR of 27.9% between  2020-2025. Lower device costs in combination with technological innovations, such as Bluetooth Low Energy (BLE) Audio, TinyML, and built in sensors will drive demand and unlock new use cases and applications such as location-based audio sharing.

ABI Research expects that the launch of WiFi6 and WiFi6e will accelerate chip shipments due to higher demand for consumer Wi-Fi enabled devices such as smart home appliances and AR/VR HMDs. “Consumers will favor those devices with updated protocols due to their promise of higher bandwidths, providing connectivity to a larger number of devices with limited interference,” Kouri notes. At the same time, BLE is a very promising wireless technology and is anticipated to account for 38% of total Bluetooth consumer device shipments, with the most important product categories including speakers, smartwatches, and hearables by 2025, growing from 19% in 2020.

“As the market gradually recovers from the pandemic, tech giants will continue the development of Merger and Acquisition deals in game-changing areas like artificial intelligence (AI), machine learning (ML), and voice and sound recognition in order to design smarter consumer products and services to remain completive in a fast-growing marketplace,” Kouri concludes.

These findings are from ABI Research’s Consumer Technologies market update report. This report is part of the company’s Consumer Technologies research service, which includes research, data, and ABI Insights. Depicted in a PowerPoint format, the Market Update provides a snapshot into current and future market opportunities and threats for a specific technology as well as focusing on a selected key market and associated trends.

in-vehicle-advertising-to-fall-flat-–-commerce-is-the-new-revenue-stream-for-car-makers

In-Vehicle Advertising to Fall Flat – Commerce Is The New Revenue Stream For Car Makers

April 15, 2021 Published by

 

Connected vehicle subscriptions hardly offset the costs of providing connectivity, so OEMs are looking for strategies to extract revenue from their installed base. In-vehicle advertising can be swiftly implemented in vehicles with a display and generate attractive profitability. However, OEMs have had reservations due to the harm it could cause to their brand reputation. Instead, they are gaining interest in commerce platforms developed to promote businesses offering in-vehicle payment via non-intrusive smart personalization. ABI Research, a global tech market advisory firm, estimates that carmakers revenues with in-vehicle payments made via the vehicle HMI will reach US$3.94 billion in 2026.

“Today, vehicle connectivity is nearly imperative. Nevertheless, it incurs cost to the automaker, and there is still no consensus about who should pay for it. High churns from customers who see no value in renewing their subscriptions are the elephant in the room that OEMs are still trying to avoid by continuously extending free trial periods,” explains Maite Bezerra, Smart Mobility & Automotive Research Analyst at ABI Research. ” In-vehicle advertising and payments are two possible strategies to monetize from the connected vehicles’ installed base by repurposing components and technologies already available in-car, without significant upfront investments.”

With advertising, OEMs would profit from ads displayed at the vehicle’s touchscreen, while drivers benefit from a free ad-based connectivity subscription. The concept finds better reception among entry and medium-level vehicle owners used to advertising-based models from apps like Pandora and Spotify. “However, unlike phones, vehicles are expensive goods, and customers who made such a significant investment will likely get frustrated by constantly seeing ads on their screens. While in-vehicle ads can generate extra revenue for OEMs even in low-adoption scenarios, the potential reputation damage can easily lead to vehicle sales losses that outweigh the potential revenue,” Bezerra explains. Although not the best-suited strategy in the traditional vehicle ownership model, ads could find traction among subscription-based ownership models or in usage-based MaaS fleet scenarios.

Even in a low user adoption scenario, in-vehicle payments made via the vehicle touchscreen can generate a higher revenue than advertising, and the chances of brand reputation damage are minimal. It can even offset connectivity costs in scenarios with large end-user adoption, but that demands a compelling digital experience to drive revenue-generating touchpoints. Today’s in-vehicle commerce solutions (e.g., GM Marketplace and FCA’s Uconnect Market) have a fair amount of friction with fragmented payment methods and requiring drivers to download apps and create an account with individual merchants. Therefore, OEMs are currently working with marketplace vendors (e.g., Cerence, Xevo, Telenav, and SiriusXM) to provide a better experience to the final user by integrating the payment features with vehicle sensor analytics (e.g., vehicle location, fuel level, or driver identity) to enable context-aware use cases. Nevetheless, projects have been delayed due to the COVID-19 pandemic. Significant deployments should be expected between 2023 and 2024.

“In-vehicle commerce platforms will have to compete against the several well-established remote payment solutions available today, such as contactless cards, smartphones, and wearables, as well as smartphone mirroring. Thus, they must offer a compelling user experience to achieve the high adherence levels required for reasonable profitability. In this regard, the increasing adoption of Android OS could help OEMs increase touchpoints with their embedded systems,” Bezerra concludes.

These findings are from ABI Research’s Automotive In-Vehicle Advertising and Commerce application analysis report. This report is part of the company’s Smart Mobility & Automotive research service, which includes research, data, and ABI Insights. Based on extensive primary interviews, Application Analysis reports present in-depth analysis on key market trends and factors for a specific technology.

Latest Members

Recent AchievementsYou must be logged in to view earned achievements

What is a Wire Coin?

Find connections

Who is online

Latest Hashtags

#artificialintelligence #betting #blockchain #casino #esports #fintech #gaming #hiptherfestival #hipthers #igaming #slots #technology