Monthly Archives: August 2021

The accelerating pace of global change is driving a biodiversity extinction crisis (1) and is outstripping our ability to track, monitor, and understand ecosystems, which is traditionally the job of ecologists. Ecological research is an intensive, field-based enterprise that relies on the skills of trained observers. This process is both time-consuming and expensive, thus limiting the resolution and extent of our knowledge of the natural world. Although technology will never replace the intuition and breadth of skills of the experienced naturalist (2), ecologists cannot ignore the potential to greatly expand the scale of our studies through automation. The capacity to automate biodiversity sampling is being driven by three ongoing technological developments: the commoditization of small, low-power computing devices; advances in wireless communications; and an explosion in automated data-recognition algorithms in the field of machine learning. Automated data collection and machine learning are set to revolutionize in situ studies of natural systems.

Automation has swept across all human endeavors over recent decades, and science is no exception. The extent of ecological observation has traditionally been limited by the costs of manual data collection. We envision a future in which data from field studies are augmented with continuous, fine-scale, remotely sensed data recording the presence, behavior, and other properties of individual organisms. As automation drives down costs of these networks, there will not be a simple expansion of the quantity of data. Rather, the potential high resolution and broad extent of these data will lead to qualitatively new findings and will result in new discoveries about the natural world that will enable ecologists to better predict and manage changing ecosystems (3). This will be especially true as different types of sensing networks, including mobile elements such as drones, are connected together to provide a rich, multidimensional view of nature. Given the role that biodiversity plays in lending resilience to the ecosystems on which humans depend (4), monitoring the distribution and abundance of species along with climate and other variables is a critical need in developing ecological hypotheses and for adapting to emerging global challenges.

Ecosystems are alive with sound and motion that can be captured with audio and video sensors. Rapid advances in audio and video classification algorithms can allow the recognition of species and labeling of complex traits and behaviors, which were traditionally the domain of manual species identification by experts. The major advance has been the discovery of deep convolutional neural networks (5). These algorithms extract fundamental aspects of contrast and shape in a manner analogous to how we and other animals recognize objects in our visual field. Applied to audio signals, these neural networks are highly effective at classifying natural and anthropogenic sounds (6). A canonical example is the classification of bird songs. Other acoustic examples include insects, amphibians, and disturbance indicators such as chainsaws. Naturally, these algorithms also lend themselves to species identification from images and videos. In cases of animals displaying complex color patterns, individuals may be distinguished, allowing minimally invasive mark recapture, an important tool in population studies and conservation (7). Beyond sight and sound, sensors can target a wide range of physical, chemical, and biological phenomena. Particularly intriguing is the possibility for widespread environmental sensing of biomolecular compounds that could, for example, allow quantification of DNA-scapes by means of laboratory-on-a-chiptype sensors (8).

Several technological trends are shaping the emergence of large-scale sensor networks. One is the ongoing miniaturization of technology, allowing deployment of extended arrays of low-power sensor devices across landscapes [for example, (9)]. In many cases, these can be solar-powered in remote locations. The widespread availability of computer-on-a-chip devices along with various attached sensors is enabling the construction of large distributed sensing networks at price points that were formerly unattainable. Similarly, the ubiquitous availability of cloud-based computing and storage for back-end processing is facilitating large-scale deployments.

Small, ruggedized sensors, such as this passive acoustic recorder, enable remote monitoring of biodiversity. New technologies are enabling such devices to process data and transmit information via wireless networks.

Another trend is advancements in wireless communications. For example, the emerging internet of things (10) enables low-power devices to establish ad hoc mesh networks that can pass information from node to node, eventually reaching points of aggregation and analysis. The same technology used to connect smart doorbells and lightbulbs can be leveraged to move data across sensor networks distributed across a landscape. These protocols are designed for low power consumption but may not have sufficient bandwidth for all applications. An alternative, although more power hungry, is cellular technology, which has increasing coverage globally. In remote locations, where commercial cellular data services may not be available, researchers can consider a private cellular network for on-site telemetry and satellite uplinks for internet streaming. However, in the near term, telecommunications costs and per-device power requirements may nonetheless prove prohibitive in certain high-bandwidth applications, such as video and audio streaming. An alternative for sites where communications bandwidth is limited by cost, isolation, or power constraints is edge computing (11). In this design, computation is moved to the sensing devices themselves, which then transmit filtered or classified results for analysis, greatly reducing transmission requirements.

One more trend is the advancement of machine-learning methods (12) that can classify and extract patterns from data streams. Much of this technology has been commoditized through intensive development efforts in the technology sector that have resulted in widely available software libraries usable by nonexperts. The aforementioned convolutional neural networks can be coded both to segment data into units and to label these units with appropriate classes. The major bottleneck is in training classifiers because initial training inputs must be labeled manually by experts. Although labeled training sets exist in some domainsmost notably, image recognitionfuture analysts may be able to skip much of the training step as large collections of pretrained networks become available. These pretrained networks can be combined and modified for specific tasks without the requirement of comprehensive training sets. Of particular interest from the standpoint of automation are new developments in continual learning (13), in which networks adjust in response to changing inputs. This holds the promise of automating model adaptation for detecting emerging phenomena, such as species shifting their ranges in response to climate change or other shifts in ecosystem properties.

Ecologists could leverage these developments to create automated sensing networks at scales previously unimaginable. As an example, consider the North American Breeding Bird Survey, a highly successful citizen-science initiative running since the late 1960s with continental-scale coverage. Expert observers conduct point counts of birds along routes, generating data that have proved invaluable in tracking trends in songbird populations (14). Although we hope to see such efforts continue, imagine what could be learned if, instead of sampling these communities once per year, a long-term, continental-scale songbird observatory could be constructed to record and classify bird vocalizations in nearreal time along with environmental covariates. Similar networks could use camera traps or video streams to reveal details of diurnal and seasonal variation across diverse floras and faunas. As with all sampling methods, sensing networks will not be without biases in sensitivity and discrimination, yet they hold the extraordinary promise of regional sampling of biodiversity at the organismal scale, something that has proven difficult, for example, by using traditional satellite-based remote sensing. These efforts would complement ongoing development of continental-scale observatories in ecology [for example, (15)] by increasing the spatial and temporal resolution of sampling.

Acknowledgments: Our perspective on autonomous sensing was developed with the support of the Stengl-Wyer Endowment and the Office of the Vice President for Research Bridging Barriers programs at the University of Texas at Austin, and the National Science Foundation (BCS-2009669). Comments from members of the Keitt laboratory, Planet Texas 2050, A. Wolf, and M. Abelson were invaluable in refining our ideas.

View post:

Ecology in the age of automation - Science Magazine

INDUSTRY INSIGHT

As this fiscal year wraps up, many agencies are planning their response to compliance reporting requirements. Meeting these requirements -- particularly in advance of an audit -- can be incredibly time-consuming. While the Defense Department has made managing risk easier through Security Technical Implementation Guides (STIGs), its still dependent upon IT staff to help ensure their systems are continuously secure and compliant -- throughout the year, not just at a point in time.

Government IT systems are complex, budgets are limited and threats are constantly evolving. Ensuring that those systems have the right security controls, processes and documentation in place to demonstrate compliance with security standards can be challenging, but the effort is highly manageable, especially with automation. Lets consider how government IT professionals can use automation to take the time and guesswork out of compliance.

The problem with STIGs

A STIG is a set of security hardening standards and maintenance processes for networks, systems and platforms all DOD IT assets must comply with. There are hundreds of possible STIGs -- each with thousands of rules that must be followed -- and the number only continues to rise as new systems, versions and updates come online.

Monitoring server and network configurations against these compliance policies can be cumbersome. Even with the best change-control processes, it requires an army of people to manage and track all the configuration changes happening within the IT infrastructure. If a system has a particular STIG applied to it and happens to deviate from that control, how would system and network administrators know?

This is particularly problematic because these changes are happening all the time. A system or device can deviate from a STIGs expected baseline configuration for any number of reasons -- such as a system update or when a patch is applied to a vulnerability. Sometimes the deviation is deliberate. For example, an application may not run properly without introducing permission or authorization settings that deviate from the STIG. In each of these instances, administrators must create an exception to the STIG. They must also explain and document the exception in preparation for an audit -- a painstaking process.

These manual, time-consuming compliance tasks can take weeks and cost a significant amount of taxpayer money to implement across applications, servers and networks.

How automation can help ease compliance

Automation is critical to lessening the compliance burden on IT pros and allows them to focus on other priorities.

Applications, systems and devices are constantly in flux, and staying on top of any configuration drift is challenging. This isnt just a compliance issue. Any configuration changes in the IT infrastructure can lead to security breaches, outages and slowdowns.

However, with automation, administrators dont have to monitor each system in a cache of thousands of IT assets for potential configuration changes. Instead, the moment a configuration starts to drift from baseline security tools, monitoring tools detect the change and proactively notify administrators in near-real-time. IT teams also have visibility into who has changed the configurations, what changed and the related performance impact.

With this insight, they can troubleshoot faster, eliminate vulnerabilities, improve security, build in exceptions and demonstrate compliance far more effectively and efficiently than manual processes will allow.

Automation can also remediate the tedious task of compliance reporting. Administrators can quickly produce FISMA and STIG reports from their configuration templates and easily generate audit documentation and reports -- work that would otherwise take weeks to complete.

Compliance automation can help break down the barriers between security and operations teams. System and network administrators must know their systems are configured in accordance with security policy, but they often lack access to the right tools. However, with the ability to monitor server and device configurations against compliance requirements, they can quickly identify and fix issues without burdening their peers in the security operations center.

Stepping up to automated compliance

Mitigating security risks is one of the most important tasks IT and network administrators undertake. Its also one of the most complex, time consuming and costly -- particularly as it relates to compliance. This is where automation can really shine -- helping the entire federal IT team achieve compliance and deliver compliance reporting while lightening their load.

About the Author

Brandon Shopp is VP of product strategy with SolarWinds.

View original post here:

How automation takes the time and guesswork out of security compliance - GCN.com

The Transform Technology Summits start October 13th with Low-Code/No Code: Enabling Enterprise Agility. Register now!

The number one reason knowledge workers regardless of role use automation is to save time, according to a new survey by Zapier. Marketers save the most time due to automation tools, an average of 25 hours saved each week, followed by IT professionals at 20 hours, customer service representatives at 16 hours and HR professionals at eight hours. The amount of time saved translates into each roles loyalty toward automation.

For example, marketers (86%), IT professionals (88%), and customer service representatives (79%) are also the most likely to say that theyll implement automation software in their next role. Most surprisingly, nearly 30% of knowledge workers say they received a raise or promotion as a result of using automation software. Additionally, knowledge workers say using automation tools improved their morale (35%), competence (34%), and confidence (32%) at work. Employees who dont have to stress about tedious tasks, inaccurate data, and miscommunication can help create a happier and more confident workforce.

How you use automation and how it benefits you depends a lot on your role. Accountants found that reduced errors (33%) was the primary benefit of automation. Given the detail-oriented nature of this role that makes sense. IT professionals said that receiving a promotion (36%) was the primary benefit. IT professionals are expected to help streamline other peoples work, so it makes sense that automation could help them get a promotion. Sales and customer service representatives cited increased confidence (35%) as one of the primary benefits. These high-pressure and often micro-managed roles are benefitting from the confidence automation can provide.

More than half of knowledge workers use automation tools every day. Marketers are leading in automation usage, which means there is considerable opportunity for other roles to catch up.

Read the full report by Zapier.

Visit link:

Zapier: 60% of knowledge workers use automation to save time - VentureBeat

UiPath came seemingly out of nowhere in the last several years, going public last year in a successful IPO during which it raised more than $527 million. It raised $2 billion in private money prior to that with its final private valuation coming in at an amazing $35 billion. UiPath CEO Daniel Dines will be joining us on a panel to discuss automation at TC Sessions: SaaS on October 27th.

The company has been able to capture all this investor attention doing something called robotic process automation (RPA), which provides a way to automate a series of highly mundane tasks. It has become quite popular, especially to help bring a level of automation to legacy systems that might not be able to handle more modern approaches to automation involving artificial intelligence and machine learning. In 2019 Gartner found that RPA was the fastest growing category in enterprise software.

In point of fact, UiPath didnt actually come out of nowhere. It was founded in 2005 as a consulting company and transitioned to software over the years. The company took its first VC funding, a modest $1.5 million seed round, in 2015, according to Crunchbase data.

As RPA found its market, the startup began to take off, raising gobs of money, including a $568 million round in April 2019 and $750 million in its final private raise in February 2021.

Dines will be appearing on a panel discussing the role of automation in the enterprise. Certainly, the pandemic drove home the need for increased automation as masses of office workers moved to work from home, a trend that is likely to continue even after the pandemic slows.

As the RPA market leader, he is uniquely positioned to discuss how this software and other similar types will evolve in the coming years and how it could combine with related trends like no-code and process mapping. Dines will be joined on the panel by investor Laela Sturdy from CapitalG and ServiceNows Dave Wright, where they will discuss the state of the automation market, why its so hot and where the next opportunities could be.

In addition to our discussion with Dines, the conference will also include Databricks Ali Ghodsi, Salesforces Kathy Baxter and Puppets Abby Kearns, as well as investors Casey Aylward and Sarah Guo, among others. We hope youll join us. Its going to be a stimulating day.

Buy your pass now to save up to $100. We cant wait to see you in October!

Is your company interested in sponsoring or exhibiting at TC Sessions: SaaS 2021? Contact our sponsorship sales team byfilling out this form.

Excerpt from:

UiPath CEO Daniel Dines is coming to TC Sessions: SaaS to talk RPA and automation - TechCrunch

DUBLIN, Aug. 20, 2021 /PRNewswire/ -- The "Global Industrial Control & Factory Automation Market by Solution (SCADA, PLC, DCS, MES, Industrial Safety, PAM), Component (Industrial Robots, Industrial 3D Printing, Process Analyzer, Machine Vision, HMI), Industry, Region - Forecast to 2026" report has been added to ResearchAndMarkets.com's offering.

The industrial control & factory automation market size is expected to grow from USD 133.1 billion in 2021 to USD 197.8 billion by 2026; it is expected to grow at a CAGR of 8.2% from 2021 to 2026

The key factors driving the growth of the market include adoption of emerging technologies such as IoT and AI in industrial environments, emergence of connected enterprises and requirement of mass manufacturing of products, government initiatives to promote industrial automation, emphasis on industrial automation and optimum utilization of resources, and fiscal policies formulated by regional financial institutions to keep manufacturing facilities floating amidst COVID-19 crisis.

Market for industrial sensors to account for largest market share in component during the forecast period

The industrial sensors segment is expected to hold the largest share of the industrial control & factory automation market. The growth of the industrial sensors segment is driven by the growing adoption of Industry 4.0 and IIoT, and the growing wireless sensors market.

Predictive maintenance is expected to offer lucrative opportunities to the players in the industrial sensors market in the coming years. Predictive maintenance is enabled by 3 major solution enhancements over a traditional maintenance schedule: capturing sensor data, facilitating data communications, and making predictions. As sensors are an important part of predictive maintenance solutions, the demand for industrial sensors is expected to increase significantly in the coming years.

PAM solution to grow at the highest rate during the forecast period

The PAM segment is expected to grow at the highest CAGR during the forecast period. The growth of this segment can be attributed to the increasing deployment of PAM solutions in process and discrete industries to build a comprehensive data repository related to different equipment installed in these plants, right from their uptime performance to their life cycle cost assessment.

Oil & gas process industry to account for largest market share during the forecast period

Industrial control & factory automation solutions can enable the oil & gas industry to monitor the facilities remotely and gain insights into daily inventory and equipment conditions. Remote monitoring can compensate for the shortage of skilled workforce for collecting equipment data. It also reduces the risk to the lives of employees and improves the overall safety and efficiency of industrial workers.

Medical devices discrete industry to grow at highest CAGR during the forecast period

In the medical devices industry, industrial control & factory automation solutions help improve manufacturing processes, planning, technology assessment, third-party services, and remote support. Industrial control & factory automation technologies also help reduce recalls and wastes and increase the profitability of the companies engaged in the manufacturing of medical devices due to precision in manufacturing.

APAC is expected to capture largest market size during the forecast period

The APAC industrial control & factory automation is projected to capture the largest market size, driven by the increasing adoption of automation technologies across industrial sectors in China and India. Factory automation is increasing in China, due to high labor wages and the presence of a large number of automotive manufacturing plants. Growing population, rising standards of living, and developing economies have led to the rising demand for energy.

It is estimated that APAC could drive approximately 65% of the global energy demand by 2035, with China and India collectively expected to fulfill 40% of the demand. Oil and gas companies in North America and Europe have started investing in APAC to fulfill the growing energy demand. The increasing energy demand would lead to the development of the energy sector, including oil & gas and power industries. This, in turn, would generate demand for automation products in the APAC region.

Major players operating in the industrial control & factory automation market include ABB Ltd. (Switzerland), Endress+Hauser AG (Switzerland), Emerson Electric Co. (US), General Electric (US), Rockwell Automation, Inc. (US), Schneider Electric SE (France), Siemens AG (Germany), Mitsubishi Electric Corp. (Japan), Honeywell International Inc. (US), and Yokogawa Electric Corp. (Japan).

Market Dynamics

Drivers

Restraints

Opportunities

Challenges

Case Studies

Technology Analysis

Company Profiles

Key Players

Other Players

For more information about this report visit https://www.researchandmarkets.com/r/o75mta

Media Contact:

Research and Markets Laura Wood, Senior Manager [emailprotected]

For E.S.T Office Hours Call +1-917-300-0470 For U.S./CAN Toll Free Call +1-800-526-8630 For GMT Office Hours Call +353-1-416-8900

U.S. Fax: 646-607-1904 Fax (outside U.S.): +353-1-481-1716

SOURCE Research and Markets

http://www.researchandmarkets.com

Continue reading here:

Global Industrial Control & Factory Automation Market Report 2021: Market is Expected to Reach $197.8 Billion by 2026 - Opportunities in the...

What You Should Know:

78 percent of health systems are currently using or are in the process of implementing automation in their revenue cycle operations, according to recent survey results from AKASA, a South San Francisco-based revenue cycle management automation company. The key findings signal automation in healthcare is no longer an emerging trend but is mission-critical for driving efficiency and cost-effectiveness in revenue cycle operations.

According to the survey, health systems (versus hospitals) are statistically more likely to be currently using or implementing automation tools in their revenue cycle operations. Survey results also show that as the size of the organization increases so does their use of automation tools with the largest healthcare providers, those with $1B $10B net patient revenues, most actively using or implementing these tools.

COVID-19 Impact on Revenue Cycle

COVID-19 has placed many healthcare organizations under intense cash-flow pressure and created volatile claim volumes and workloads for revenue cycle teams. These dynamics are driving more revenue cycle leaders to look to automation to provide flexibility and resiliency in their operations while minimizing their organizations cost to collect. The survey also found that 37% of organizations currently not using automation plan to do so this year or sometime in 2022.

Increase Focus of Digital Transformation in Healthcare

Commissioned by AKASA, the survey fielded responses from nearly 400 chief financial officers and revenue cycle leaders at hospitals and health systems across the United States through the Healthcare Financial Management Associations (HFMA) Pulse Survey program between May 27, 2021 and June 28, 2021.

Results demonstrate that the increasing focus on digital transformation efforts in healthcare has driven the adoption of automation to help manage claims, billing and reimbursement processes. The majority of health systems and hospitals, (more than 66 percent) say they are now using or implementing automation in their revenue cycle operations.

The findings underscore that automation serves as a backbone for healthcare financial leaders looking to streamline complex staff workflows, said Malinka Walaliyadde, co-founder and CEO of AKASA. The opportunity going forward for provider organizations is to expand their ambitions and scope for automation. Instead of identifying dozens of small, discrete use-cases and never getting past the first few due to high setup and maintenance costs, leaders should consider solutions that can be deployed rapidly with minimal disruption. The goal is foundational, end-to-end automation for entire functions, driving giant leaps in efficiency.

Read this article:

Provider Adoption of Automated Revenue Cycle Operations On The Rise - HIT Consultant

Advertisers need to come together with media, measurement and ad-tech companies to support the growth in advanced TV. Their partnerships will lead to greater automation and better outcomes that drive more investment in advertising as linear TV and digital video converge.

Kevin Lemberg, head of partnerships for advertising solutions at Comcast Technology Solutions

There has to be some sort of unification and some sort of common language and goals between the partners within a solution or technology that were offering out to the industry, he said. Partnerships are going to be very important to round out the technology offering and the solutions for the industry in order for us to move forward.

Jen Soch, executive director of specialty channels at WPPs GroupM

Were really seeing an idea where we can be with addressable and CTV part of the main video recommendation that goes into what were doing with a client, and look at it more holistically. she said. I do see a lot more interest in bringing it [addressable and CTV] very much to the forefront and being a bigger part of their overall play.

Kelly Abcarian, executive vice president of measurement and impact at NBCUniversal

Interoperability across linear and digital without losing the value of premium content along the way is going to be so critical, she said. If we lose and swing the pendulum too far to audiences only, imagine content being cheapened over the coming years and basically creating a society that the value is placed on audiences alone.I look forward to working with the industry on how, as we try to equivalize and become more interoperable, we dont lose the value of premium content.

Kristine Bayles, vice president of advanced advertising sales at AMC Networks

Addressable TV enables us to get the insights into communication and driving deeper understanding in the industry, she said. We all know TV is important, but CTV and VOD is just as importantViewership is truly fragmented now, and its not that less people are consuming, theyre just consuming differently. We need to understand this, and move forward with converged impressions.

Mark Marshall, president of advertising and partnerships at NBCUniversal

Our goal on that [automated workflows] is to work with our partners on the agency side be able to get rid of about 30% of the manual work that we do, he said. How do we find different APIs [application programming interfaces] and different ways to interact, and take out some of the manual elements to allow us to move faster and hopefully improve margins for clients.

Nicole Whitesel, executive vice president of advanced TV and client success at Publicis Media

We need systems that collaborate tools that talk to each other, data that can break down those walls, IDs that can understand each other, she said. Better sharing of that data enables us to have conversations with our clients about outcomes, and outcomes that deliver change to their business, and outcomes that change the way they decide media mix.

Vicky Fox, chief planning officer at OMD UK

Weve moved from a place where people were quite wedded to a linear schedule, she said. Self-scheduling is going to be the norm for everybody. Anybody who switches on the TV and either looks at their connected TV menu or their EPG [electronic programming guide] can see how much has changed, because some of the linear schedules may take second place.

Richard Nunn, vice president and general manager of advertiser solutions at Comcast Technology Solutions

Through automation and understanding what has worked and what hasnt in more real time across channel that in principle, should mean a greater ROI across what is a fragmented channel base, he said. Theyll drive that solution a lot more efficiently because of technology.

You are watching Whats Next For Advertisers? Key Changes That Will Drive The Industry Forward, a Beet.TV leadership series presented by Comcast Technology Solutions. For more videos, please visit this page. For Comcast Technology Solutions paper on these topics, please visit this link.

Editors Note: Special thanks to Jon Watts who collaborated and reported for this series.

View post:

Partnerships, Automation Underpin Future of Advanced TV: Execs from Comcast Technology Solutions, , GroupM, NBCUniversal, AMC, Publicis, OMD Beet.TV...