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700-802 IoT Manufacturing Account Manager

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700-802 exam Dumps Source : IoT Manufacturing Account Manager

Test Code : 700-802
Test name : IoT Manufacturing Account Manager
Vendor name : Cisco
exam questions : 35 real Questions

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Cisco IoT Manufacturing Account Manager

IoT in Manufacturing: Insights and most efficient Practices | real Questions and Pass4sure dumps

IoT Webcast Manufacturing net

these days, the second of a two-part webcast collection on ‘The internet of issues ’ (IoT) wrapped with a deep dive on the very actual enterprise benefits and outcomes which are enabled when IoT is thoroughly utilized to Manufacturing operations. probably the most audio system, David Gutshall, Infrastructure Design supervisor at Harley-Davidson Motor enterprise, highlighted many advantages he’s skilled with deployments of the Converged Plant-broad Ethernet solution architecture from Cisco and Rockwell Automation. in the webcast, David spoke of “more desirable manufacturing flexibility throughout the deliver chain, where … they are able to collate statistics throughout the factory (and enterprise) … and hold skilled a considerable discount in downtime.”  He described that with an IP-enabled connected manufacturing unit, “what used to consume hours or days to triage and troubleshoot issues now takes seconds.” expanding on the topic matter, David eminent “once they bring a recent machine on-line, it very nearly works with the community out-of-the-container,” yielding more advantageous flexibility and vastly cutting back recent model NPI (New Product Introduction) cycles and time to market.

similar organizations, affection established Motors, hold leveraged this industrial automation and controls system (IACS) structure, which GM calls ‘Plant flooring handle community’ (PFCN), to slice back downtime with the aid of as a lot as seventy five% and to power out lots of of $millions in plant engineering, operations and upkeep prices linked to manufacturing unit expansions and modernizations. each GM and Harley establish one of the most largest benefits of a standardized yet springy manufacturing facility automation infrastructure is the acceleration of NPI choices and evolution into recent markets. over the past decade, GM with companions has been capable of profit a number one share of passenger cars produced in China, Brazil and other emerging markets. And as Harley rolls out their lately announced LiveWire electric bike, i believe that a vital share of their manner includes the American manufacturing renaissance vision for a dynamic, fun, bendy manufacturing facility of the long run. consume a witness at this inspirational video from Harley describing the modernization and transformation of their present York Manufacturing Facility:

David Gutshall described birthright through the half II webcast how IoT in manufacturing has enabled “pass-purposeful knowledge, a flattening of the firm.” As illustrated in the above video, David additionally elaborated on the illustration of Harley-Davidson’s implementation of a ‘visible manufacturing unit’, the status “dashboards displaying the equal views, together with key sensor … (and) TAC time” advice assist to collect everysingle employees engaged, aligned and committed. When protection, controls engineering and IT are everysingle empowered with a “single pane of glass” visibility to greater correct, precise-time information, there is a cultural shift to travail better, greater readily together against customary dreams.

The alternatives and consequences for IoT inside manufacturing involve improving time to market, asset utilization, manufacturing flexibility, reducing complete expenses of ownership, and managing and mitigating operational risks. Enabling technologies equivalent to converged plant-broad IACS networking solutions are in reality starting to alternate the panorama for producers grappling with increased commerce challenges to manage expenses, drive exceptional throughput and improved exploit risks. Exemplified with the aid of Harley, the affect of IoT is tons broader than just operational metrics or recent connectivity.  What IoT can accommodate is the shift toward cultural empowerment of producing personnel to rotate into proper partners to the company.

Please consume the time to view both share I and share II of the Manufacturing.internet webcast sequence and share with me your ideas, experiences and enterprise results associated with IoT in manufacturing, and the course the convergence of community and know-how are enabling cultural and organizational convergence and transformations. thank you for taking the time to study this blog.


international AI in Manufacturing to witness 51.31% CAGR from 2019-2027 | real Questions and Pass4sure dumps

element Roberts, WA and Vancouver, BC - March 1, 2019 ( Newswire) (, a world investor information supply masking artificial Intelligence (AI) brings you state-of-the-art version of The AI Eye- gazing stock information, deal tracker and developments in artificial intelligence.

take heed to modern day podcast:

The #AI Eye: $IBM ( $IBM) reveals Maximo Asset efficiency administration and Cisco ( $CSCO) and Ricoh associate to Empower Digital workplaces

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world AI in Manufacturing to peer fifty one.31% CAGR from 2019-2027

document Linker has lately published analysis indicating that the global AI in manufacturing market is projected to exhibit a compound annual extend fee (CAGR) of fifty one.31 p.c in the forecast length 2019-2027. An excerpt from the file description reads:

The current trend of automation and records trade in manufacturing applied sciences is heralded due to the various components just affection the difficult geopolitical state of affairs, growing archaic workforce and rising wages in automation expertise primarily within the rising economies of certain international locations. here's termed as the fourth industrial revolution or trade four.0. The confined being of knowledgeable personnel in information science coupled with considerations concerning records privateness & safety is expected to restrict the boom of the market in the world enviornment. information scientists combine their potential in designing, constructing & working towards synthetic intelligence & know-how, whose absence may antecedent principal losses to the marketers.

IBM displays Maximo Asset performance administration and Cisco and Ricoh associate to Empower Digital places of work shares discussed: (NYSE:IBM) (NasdaqGS:CSCO) (OTC:RICOY)

IBM (NYSE:IBM) has introduced a brand recent portfolio, known as Maximo Asset performance administration, to support asset intensive companies, combining IoT options with AI and advanced analytics. according to the clicking unencumber, "the respond is designed to aid agencies to lower charges and reduce the risk of failure from actual property comparable to motors, manufacturing robots, generators, mining equipment, elevators, and electrical transformers". Kareem Yusuf, widely wide-spread manager, IBM Watson IoT mentioned:

"it be necessary for organizations to believe about how advantageous their protection practices are. With the launch of its recent Asset performance administration options, IBM is helping businesses gain perception-pushed choices with an built-in portfolio of superior analytics and AI capabilities to support them enrich operational effectiveness and effectivity. Maximo APM is designed to boost a company's present commercial enterprise Asset administration apparatus with the aid of addressing everysingle aspects of asset efficiency together with health, predictive upkeep and restore optimization."

Cisco systems, Inc. (NasdaqGS:CSCO) has entered a strategic partnership with Ricoh business, Ltd. (OTC:RICOY) to "empower digital places of travail that convey increased productivity in a greater cozy atmosphere". An excerpt from the announcement reads:

with the aid of combining RICOH smart Integration and Cisco cloud security options beneath this partnership, Cisco and Ricoh will connect, the exhaust of Cisco Meraki, the RICOH IM C sequence of subsequent-technology multi-useful printers and different workplace contraptions seamlessly and securely with assorted cloud functions. This solution will reduce the time required for implementation, operation, and administration. additionally, through bringing collectively RICOH smart Integration with Cisco's guidance leakage detection/prevention and different superior authentication facets, the respond will aid approaches that require greater security degrees.

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Cisco: global cellular Networks Will aid greater than 12 Billion | real Questions and Pass4sure dumps

SAN JOSE, California, Feb. 19, 2019 /PRNewswire/ -- on the inception of Cisco's cellular visual Networking Index (VNI) Forecast more than a decade in the past, cell (or cellular) site visitors represented less than five p.c of complete IP site visitors crossing global networks. these days, the office and reliance positioned on cell networking has dramatically elevated.

there was global upward thrust in cellular entry for patrons and commerce clients. The accelerated gain and excellent of mobile broadband has fostered a apparently insatiable demand for cellular communications, media and a wide range of mobile IoT functions.

based on this year's forecast update (2017 – 2022), mobile traffic will be on the verge of reaching an annual Run price of a zettabyte through the finish of the forecast duration. by course of 2022, cellular traffic will depict essentially 20 % of international IP site visitors and should gain 930 exabytes annually. it really is pretty much 113 times more than everysingle world cellular site visitors generated just ten years prior, in 2012.

cellular applied sciences continue to connect more people and issues than ever before. In 2017, there hold been five billion cellular clients global, but over the next five years, that quantity will extend by half one thousand million to 5.5 billion clients, which represents about 71 p.c of the global population. via 2022, there can be greater than 12 billion mobile-in a position gadgets and IoT connections (up from about nine billion cell-ready instruments and IoT connections in 2017). through 2022, mobile networks will support greater than eight billion very own cellular instruments and four billion IoT connections.

The forecast replace additionally anticipates ongoing efforts by means of mobile carriers worldwide to extend cell network efficiency. The commonplace international cell community speeds will raise more than three-fold from 8.7 Mbps in 2017 to 28.5 Mbps with the aid of 2022. common cellular speeds range drastically by course of geographic locations as 5G adoption begins to ramp up in some regions.

Key Predictions

2G, 3G, 4G, 5G and LPWA Connection Share:

  • In 2017, Low-vigour, vast-area (LPWA) networks supported 1.5 % of cell devices/M2M connections, 2G supported 34 p.c of international mobile gadgets/M2M connections; 3G supported 30 % of global cell instruments/M2M connections; and 4G supported 35 % of global mobile instruments/M2M connections.
  • by 2022, LPWA networks will guide 14 p.c of mobile instruments/M2M connections, 2G will aid eight % of world cell devices/M2M connections; 3G will aid 20 % of global mobile instruments/M2M connections; 4G will aid fifty four percent of global cell gadgets/M2M connections; 5G will guide three percent of world cell gadgets/M2M connections (about 422m 5G connections globally).
  • 5G:  

  • by means of 2022, 5G connections will symbolize over three p.c of complete cell connections (more than 422 million international 5G contraptions and M2M connections) and may account for nearly 12 p.c of international cellular statistics traffic.
  • by using 2022, the timehonored 5G connection (22 GB/month) will generate about 3X extra site visitors than the common 4G connection (eight GB/month).
  • WiFi: traffic Offload from cellular Networks (cellular) to fastened Networks (WiFi)

  • In 2017, month-to-month offload site visitors (13 EB) surpassed monthly mobile/mobile traffic (12 EB).
  • In 2017, 54 % of complete cellular facts traffic turned into offloaded; by 2022, fifty nine % of complete cellular information site visitors can be offloaded.
  • 2017 total IP traffic (fixed & cellular): 48 percent Wired, forty three percent WiFi, nine p.c mobile.
  • 2022 complete IP site visitors (fastened & cellular): 29 p.c Wired, fifty one % WiFi, 20 percent cellular.
  • Globally, complete WiFi hotspots (including home spots) will grow 4X from 2017 (124 million) to 2022 (549 million).
  • "Cisco is committed to assisting community operators meet the growing to be bandwidth needs of mobile buyers, commerce users and the discrete collection of IoT functions," said Jonathan Davidson, senior vice chairman and yardstick manager, provider issuer enterprise, Cisco. "As global cellular site visitors methods the zettabyte era, they respect that 5G and WiFi will coexist as fundamental and complementary access technologies, providing key benefits to their commercial enterprise and repair issuer purchasers to extend their architectures. They seem forward to ongoing discussions with purchasers next week at mobile World Congress Barcelona on getting ready for this boom and mapping out their network structure transitions."

    Cisco mobile VNI Forecast The Cisco cellular VNI™ Forecast contains world, regional, and country-degree projections and trends associated with cellular (2G, 3G, 4G, and 5G) radio networks. the replete file comprises additional info and analysis on cellular site visitors growth, cellular instruments/connections, cell IoT via various trade verticals, cellular IPv6 adoption, cellular network performance, Wi-Fi offload from cellular instruments/connections, and cell tiered pricing (limitless and shared plans).

    Cisco cellular VNI MethodologyThe Cisco VNI™ comprehensive Forecast for 2017 to 2022 relies upon unbiased analyst forecasts and real-world network usage records. Upon this foundation are layered Cisco's own estimates for global IP site visitors and repair adoption. a particular methodology description is blanketed within the complete record. Over its 13-year background, Cisco® VNI analysis has develop into a particularly considered measure of the cyber web's increase. country wide governments, community regulators, educational researchers, telecommunications businesses, technology specialists and trade/enterprise press and analysts depend on the annual resolve to aid arrangement for the digital future.

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    IoT Manufacturing Account Manager

    Pass 4 certain 700-802 dumps | 700-802 real questions |

    IoT as a Data Driven Lab Manager | real questions and Pass4sure dumps

    The role of a lab manager is one that comes with petite downtime, as they act both as strategic managers and essentially as the tactical glue that keeps operations running. Thanks to the emergence of Smart Labs and Internet of Things (IoT) technologies, a range of novel tools hold been developed to assist with their ever more intricate responsibilities.

    This article will investigate the options for lab managers to gain replete exhaust of these technologies to support them in meeting their ongoing goals for development, as well as increasing their strategic repercussion on the overall organization.

    Managing the rush of Data

    Handling the rush of data is a central duty in science, whether this refers to tracking, recording, analysis or storage.

    As well as primary experimental data, the data sphere in the modern lab has grown to encompass inventory data, test protocols, employee training records, environmental data, instrument calibration records, and perhaps most exasperatingly, test results from various pieces of apparatus that enact not connect with one another.

    As laboratory data is stored in multiple unconnected forms, the difficulties of managing data – from collection to storage to access – are myriad. These individual pockets of data involve some records that are manually collected and logged in notebooks, complete with handwritten signatures, to other records that are entirely digital.

    Finding one’s course around – and eventually linking – these disconnected pieces of data is one of the most significant challenges faced by organizations both great and small. The difficulties and the costs are at the identical time clear-cut and opaque.

    Where comprehensive access to lab data across the enterprise is not possible, the organization is not able to gain exhaust of the replete value of the data. This access is made difficult by two serious issues:

  • Gaps: Whether these are a result of either a need of technology or resources, great data gaps are a frequent issue, either in the granularity of data collected, or an absence of other data altogether.
  • Integration: Lab data is not always cohesively linked with traditional management information systems in ways that could proffer value. This could involve linking training information with HR records, associating the costs of experimental runs with finance reports, or making certain that proper information is stored in the ERP.
  • Significant changes are soon to be felt in these areas.

    By lessening the barriers to data collection, the understanding of the Smart Lab, filled with linked, data-collection systems ranging from smart instruments to quick-witted sensors to analytics software, promises to deliver melodramatic increases in the volume of lab-produced data.

    Smart lab solutions deliver recent
 insights, enabled by automated, high-resolution data, powerful data visualizations, and integration with other systems.

    Figure 1 - Smart lab solutions deliver recent  insights, enabled by automated, high-resolution data, powerful data visualizations, and integration with other systems.

    For lab managers who consume an open view of how to gain exhaust of this recent paradigm to enhance operations, a strategic change will consume status in how they execute their roles.

    These lab managers will produce the structure through which further operational efficiency can be achieved, they will gain better informed and more meaningful judgments, and they will proffer improved strategic value to their organizations.

    Tapping the Power of the Smart Lab

    The Internet of Things (IoT) has enabled cutting edge developments in sensors, networking and computing power to enhance their homes and workplaces as well as their universal health and fitness, with innovations ranging from the Smart edifice to the Smart Home to the Quantified Self movement.

    The technologies which enabled these developments are now being introduced to the lab with the assertion that scientific studies can be improved and accelerated with the aid of recent data from recent sources.

    Smart Lab solutions share these abilities:

  • Automated Data Gathering – Making certain that teams can access any and everysingle data needed to complete their travail to the highest level.
  • High-resolution Data – When working with great data sets, tools which can effectively manage, integrate and resolve are essential. Additionally, they should be able to generate opportunities for improved analysis and more profound insights.
  • Visualization – To rapidly provide visibility into great data sets.
  • Integration – To gain certain that everysingle data can be shared between systems.
  • Continuous – 24 hour surveillance of equipment, instrumentation, methods and environmental variables eradicates data gaps, and generates huge recent data assets.
  • Comprehensive – everysingle equipment, environment, and methods can now be tracked and observed without gaps.
  • Centralized – Data from a range of systems, apparatus and workflows can be cohesively joined and cross referenced, streamlining analysis.
  • Smart systems which hold been optimized for exhaust in the lab ensure that:

  • High value assets can be monitored and safeguarded with personalized alert triggers.
  • Data from instruments can now be gathered automatically and delivered straight to the cloud for analysis, sharing and storage.
  • Experimental data can be remotely monitored and more closely managed with immediate access from any location.
  • More profound analysis is both enabled and made faster, as data from a variety of sources can be synthesized and examined for deeper insights into patterns and relationships.
  • Repeatability is enhanced when experimental results can be monitored and logged, including both experimental methods and exact environmental conditions in the research setting. This also enables optimization of the scale-up process.
  • Reports and documentation to support GLP and GMP accreditation are far simpler to collect and preserve.
  • Data on exhaust of consumables can be directly shared with purchasing systems, while incoming raw material data can be shared with manufacturing QA/QC teams.
  • Environmental efficiency is enhanced, as actual data feedback can be used to optimize environments and conditions.
  • Operational efficiency is improved through the analysis and optimization of usage and utilization patterns.
  • Strategic Long-Term Value

    From a monetary viewpoint, Smart Lab systems generally hold fairly modest costs, with the largest portion of the expenditure being in organizational planning and consideration to determine how best to fully gain exhaust of the value brought in by the systems.

    Instead of being thought of as overhead costs, required to guarantee R&D or Production quality, Smart Lab systems and the data they produce allow labs to verify their positions as vital assets in the operational and strategic well-being of an organization.

    Such systems hold the capacity to drastically alter the course science is executed, but in order to enact so, they need novel consideration from lab managers and the teams they support.

    From Lab Manager to Data Strategist | Expanding the Lab Manager Role

    Smart Lab systems proffer the chance to enhance both operations and experimental science. To enact so, they require the mind-set of both a traditional scientist and a data strategist.

    Instead of managing the problems caused by apparatus or experimental failures after an incident, Smart Lab solutions can be employed to predict possible failures, lessening downtime, as well as lessening the demand on labor for repetitive tasks, allowing teams to reorganize scant resources.

    With the added profit of new, in-depth data on process implementation, these systems can also proffer information to allow users to gain laboratory procedures more straightforward and essentially, streamline their science as a whole. The solution is to hold both the data and the tools to apply it in recent and significant ways.

    One outcome of this flood of high-resolution data is a mounting burden of data-management. This increases the significance of creating strategies for acquisition, storage, tracking, access, integration and safeguarding.

    Lab managers are not just thinking about the systems and tools required, but are also developing data-management strategies that consume into account the need to share crucial data with major stakeholders both in and out of the lab. Both the volume and value of this data are restructuring the understanding of laboratory data along a trio of trajectories:

    From Archival to Actionable

    One of the most significant offshoots of the introduction of the Smart Lab is that real-time data streams immediately transmute data from an archival concern to an actionable asset. The revolution of real-time data allows teams to know immediately whether apparatus is running within particular parameters or not, or if something needs an instant response.

    These abilities act as insurance policies of a kind, assisting with the prevention of sample loss, and allowing teams to diarize preemptive maintenance to circumvent future problems as well.

    The manner in which teams handle data and outcomes is entirely altered by the introduction of real-time data. Previously, test results from each stage of a workflow would just be archived for examination at a later date, frequently as a result of an issue that needed to be fixed.

    By consistently tracking each stage of the procedure, as well as the existing conditions, it is possible to accumulate metadata on the physical environment as well as actionable insights. Some examples are:

  • Tracking and logging temperature, humidity, air pressure and light in real time allowed a materials science research and evolution team working on a drug-delivery coating to gain insight that when the ambient humidity was above 56%, their process was unsuccessful, and that when it was below that threshold, it would succeed.
  • Accessible data displaying comprehensive apparatus performance allowed a team to rapidly assess the viability of diverse apparatus for their GLP process, and opt for a icy leeway over a freezer due to smaller fluctuations in cold-room temperature.
  • Visualizations of -80C freezer data over a month allowed a team to rapidly evaluate the condition of the apparatus and arrangement maintenance.
  • Each of these instances illustrates the quantifiable repercussion of having actionable data, whether to extend efficiency or enhance repeatability.

    From Reactive to Proactive

    Thanks to Smart Labs, with data available at everysingle times and locations, lab managers are at far less risk from occurrences that were previously outside their control. Some examples are:

  • Instruments are now equipped with sensors attached that can measure usage levels, offering the lab manager data on the levels of testing carried out on any instrument. This enables them to predict levels of consumables, schedules and frequencies of cleaning and recalibration of instruments, and even to arrangement for instrument replacement.
  • Intelligent sensor devices that constantly track temperature can be attached to lab apparatus such as oven, freezers or incubators to notify selected users when a problem occurs.Whether the issue is the result of a power outage, or simply a freezer door not properly closed, the aptitude to remotely monitor allows teams to address potentially serious situations before crucial samples or materials are irretrievably damaged.Real-time visibility also allows lab managers to track the health of apparatus over time, assisting them in detecting early warning signs of possible failure in aberrations from the customary data patterns.
  • Wireless environmental sensors proffer lab managers and staff insight into crucial variables including temperature, humidity, air pressure and light conditions. Awareness of these factors allows users to ensure that test results are being produced with consistently and are not being affected by variations in these areas.
  • With the aid of web and mobile apps, it is possible to access Smart Lab data at any time. This allows lab managers to assess conditions either on-site or remotely, providing them with the data needed to determine whether a potentially serious situation (e.g. a power outage) requires them to attend the lab out of hours, or whether an incident can be addressed remotely.
  • From Strategic to Tactical

    Thanks to novel data sources and the understanding it enables, lab data is becoming ever more strategic, allowing teams to gain better-informed decisions as processes and products progress into other sections of the organization.

  • Constantly monitored conditions, including ambient readings (temperature, humidity, pressure and light), apparatus performance, instrument use, and availability of resources allow teams to gain data-driven tactical decisions around operational procedures, investments in staff, technologies and produce versus purchase.
  • QA/QC lab managers are no longer restricted to simply providing and accepting go/no depart decisions based on test results. Instead, they can investigate for patterns of failures and endorse whatever alterations are required to alleviate/eliminate failures.Additionally, they can access results remotely, and proffer teams from several locations the capability to access results collaboratively.
  • High-resolution data allows teams to utilize more refined machine learning and data analysis approaches to cross-reference numerous data sources and to gain more insight on the factors that may hold an repercussion on lab-based work.
  • Smart Lab technologies give us better surveillance capabilities, enabling their team to be proactive about efficiency and continuous improvement initiatives.

    Lyndsey York, Lab Manager, LabCentral.

    This shared laboratory space, based in Cambridge, Massachusetts, was intended as a launch-pad for high-potential life-sciences and biotech startups, offering fully permitted laboratory and office space encompassing around 125 scientists and entrepreneurs.

    Having access to both real-time and historical data helps shape decisions, and is helpful in fact-checking intuition about what may be going on.

    Lyndsey York, Lab Manager, LabCentral.

    With the assistance of a much fuller toolset, Lab Managers are positioned to become Lab Systems Managers, comparable to Finance Managers or Sales Operations Managers, employing novel technologies to better enhance processes and accepting more strategic roles within their organizations.

    As is the case with everysingle organizational shifts, these changes will not happen immediately, but just taking the initial steps in the birthright direction allows teams to be ideally placed for future success, positioning them well ahead of those who hold not yet opened their eyes to these novel opportunities.

    About Elemental Machines

    Elemental Machines is helping scientists ameliorate experimental reproducibility and accelerate scientific discovery.

    From early research and discovery to manufacturing, everyone in biology and chemistry-based industries knows that the physical environment can affect the entire product lifecycle. What they don’t know is exactly how, or the cumulative cost of not knowing -- higher R&D expenses, slower time to market for innovative products and life-saving therapies, defer loss during manufacturing, and more.

    With a deep understanding of these issues, Elemental Machines is delivering unprecedented insight into intricate processes, helping customers refine and accelerate their travail across everysingle phases of product innovation.

    By gathering and synthesizing environmental data into actionable information, Elemental Machines provides captious insights that ameliorate transparency, repeatability and outcomes, and redeem customers time and money.

    Track contextual variables (temperature, humidity, air pressure and light) in the research lab or monitor captious apparatus performance (freezers, refrigerators, ovens, and incubators) for facile access to performance data, as well as alerts if readings are out of range.

    Sponsored Content Policy: publishes articles and related content that may be derived from sources where they hold existing commercial relationships, provided such content adds value to the core editorial ethos of News-Medical.Net which is to educate and inform site visitors interested in medical research, science, medical devices and treatments.

    What Product Managers need to Know About Industrial IoT | real questions and Pass4sure dumps

    The Internet of Things (IoT) enables disruptive transformation across multiple market segments, from consumer, enterprise, agriculture, healthcare, manufacturing, and utilities to government and cities. Industrial IoT (IIoT), a subset of the larger IoT, focuses on the specialized requirements of industrial applications, such as manufacturing, oil and gas, and utilities.

    Although IoT and IIoT share common technologies (sensors, cloud platforms, connectivity, and analytics), the similarities finish there. This article highlights key differences that product managers and buyers must know when planning industrial IoT solutions.

    10 Ways IoT Differs from Industrial IoT

    While many people assume functionality distinguishes IoT from IIoT, the reality is not that simple. A consumer IoT device may hold the identical functionality as an IIoT device, and soundless not be considered an industrial product.

    For example, a consumer and an industrial activity tracker both collect and monitor heart rate information. But the industrial tracker incorporates additional design parameters that its consumer counterpart may not have. The parameters that differentiate IoT from industrial IoT include:

  • Security
  • Interoperability
  • Scalability
  • Precision and Accuracy
  • Programmability
  • Low latency
  • Reliability
  • Resilience
  • Automation
  • Serviceability
  • As a product manager rolling out your first industrial solution, or a buyer considering a consumer IoT solution for industrial use, it’s necessary to understand the differences.

    1. Security

    Security is captious for everysingle IoT solutions, but industrial IoT solutions require more robust measures. A disruption of a elevated volume manufacturing process results in lost production costing millions of dollars per day. A takedown of the electrical grid affects economic activity for millions of people and jeopardizes national security.

    IIoT solutions employ a variety of advanced security measures, from secure and resilient system architectures, specialized chipsets, encryption and authentication, threat detection, to management processes.

    2. Interoperability

    Industrial IoT solutions must co-exist in an environment with a significant amount of legacy operations technologies (OT), including SCADA, M2M, and other purpose built manufacturing execution systems. These legacy OT systems are not going away. Industrial IoT solutions must integrate, support various protocols and data sets, and travail reliably with these manufacturing systems. Equally important, IIoT solutions must integrate with back-office enterprise resource planning (ERP) systems.

    3. Scalability

    Industrial networks are specialized great scale networks supporting tens of thousands (or more) of controllers, robots, machinery, and other purpose built applications. IIoT solutions deployed into these networks must scale seamlessly, now and later, to support tens of thousands of recent sensors, devices and controllers, as well as existing non-IoT devices. This support includes interoperability, scheduling, workflow integration, data collection, analysis, decision-making, and integration with manufacturing and commerce execution systems.

    4. Precision and Accuracy

    Industrial operations require higher levels of precision and accuracy. Automated elevated volume, elevated quicken manufacturing processes are synchronized to milliseconds. attribute assurance systems detect minute variations and consume immediate corrective actions based on those measurements. In this environment, “close enough” is not superb enough, and results in lost efficiency, downtime, and revenues. Industrial IoT solutions must support operations where elevated precision and accuracy are “business as usual”.

    5. Programmability

    Industrial and OT systems, from programmable logic controllers to machining equipment, are frequently reprogrammed and reconfigured to support recent processes. This programming is done remotely, on site or in the field. Industrial IoT solutions supporting industrial and manufacturing applications must provide the identical flexibility and adaptability to support operations.

    6. Low Latency

    In a elevated quicken continuous production system with sensors monitoring every aspect of the operation, every second matters. Anomalies must be detected, and corrective actions applied in near real time. Any detain in detection, assessment, decision-making, and execution would be costly, in terms of worker safety, product quality, costs and lost revenues. Industrial IoT solutions must similarly be built to support the low latency requirements of some industrial applications.

    7. Reliability

    Industrial systems operate in long time scales before replacement — twenty to thirty years is not uncommon. They operate in harsh environments, sometimes topic to extreme heat, cold, elevated vibration, pressure, and dust conditions. They may operate in remote locations, far away from headquarters.

    Industrial IoT solutions may be topic to the identical conditions and requirements. They must be hardened to support elevated availability, withstand elevated duty cycles, and operate reliably and within tolerance, day in, day out for years and years, with shutdowns only for maintenance.

    8. Resilience

    Mission captious industrial processes and systems, where downtime (or even access for service) is not an option, are designed with resilience in mind. A breakdown in one share of the system will not cease operations. While there may be a loss in operational capability, the tasks are taken up by backup systems, or the processes may be routed to a share of the system with extra capacity.

    Industrial IoT solutions, in mission captious operations, must support vice tolerance, or resilience capabilities in its design. From a loss of sensors to a loss of connectivity, industrial IoT systems and architectures must compensate for in-use failures, and soundless be able to satisfactorily complete its processes and operations.

    9. Automation

    Many industrial processes are highly automated from start to finish, with limited to no human intervention. IoT solutions operating in industrial environments need to support a range of autonomy requirements. This may entail edifice intelligence into the edge devices, incorporating control and automation logic in the gateway, or incorporating deep learning capabilities in the system design. In addition, it must be programmable and integrate with legacy or recent manufacturing execution systems.

    10. Serviceability

    Industrial systems must operate reliably and predictably in harsh conditions for years and years. Supporting this even of performance requires regular maintenance from in-house and realm service technicians. IoT solutions operating in industrial environments must be serviceable in order to sustain the levels of performance required. From swapping out sensors, updating firmware, to configuring gateways and servers, the aptitude to maintain industrial IoT solutions over its entire lifecycle is an essential requirement.

    Key takeaways

    Functionality is important, but isn’t the only determinant of whether an IoT solution is “industrial” ready or not. There are ten other parameters that must be considered. In reality, IoT and IIoT solutions may incorporate everysingle these parameters, but vary in what is implemented and how.

    Industrial processes impose onerous requirements on IoT solutions. Product managers must account for these additional requirements in the design and engineering. They must understand the specific exhaust cases, as well as the environments the solutions will be placed into.

    Buyers evaluating IoT solutions for industrial applications must examine the difficult questions. Today’s IIoT solutions are emerging and evolving in a very dynamic market. Vendors offering IIoT solutions may be coming from adjacent markets with solutions that may not be robust enough for everysingle industrial applications.

    Want everysingle the latest advances and tech word sent directly to your inbox?

    Microsoft eyes retail, manufacturing, health sectors in India in $5 bn IoT thrust | real questions and Pass4sure dumps

    Satya Nadella-led tech giant Microsoft plans to invest $5 billion into the Internet of Things globally for the next four years. The India division of the Windows-maker is eying a piece of that investment by providing IoT solutions to industry verticals such as manufacturing, auto, retail and healthcare in the country.

    “According to a Nasscom and Deloitte report, the IoT market in India is expected to gain $15 billion by 2020, accounting for 5% of the global market. As demand for IoT in India is emerging across industries, they hold already started investing in the space early,” Rajesh Rege, country universal manager, cloud and solutions group, Microsoft India, said.

    He added that the investment will depart towards continued innovation in its technology platform and supporting programmes. “We are continuously conducting research and evolution in key areas, including securing IoT, creating evolution tools and quick-witted services for IoT and the edge, and investments to grow their confederate ecosystem,” Rege explained.

    Microsoft’s IoT solutions

    The Redmond-headquartered company began offering its IoT solutions and services from 2016. Currently, it offers the following:

    Azure IoT Hub: This product allows customers to monitor and manage billions of IoT devices and establishes two-way communication to maintain network architecture.

    Azure IoT Central: This service provides a software-as-a-service (SaaS) interface to connect and monitor IoT assets at scale for companies that don't hold cloud solutions expertise.

    Azure IoT Edge: This solution offers a fully managed service that delivers cloud intelligence locally.

    Azure Sphere: This product securely connects microcontroller-powered devices to the cloud.

    Azure Time sequence Insights: This is an analytical service that scans billions of events streaming in from everysingle over the world in seconds.

    Azure Maps: This service combines geospatial application programming interfaces (APIs) with IoT solutions to provide customers add maps and search route traffic capabilities.

    Other services such as Azure Machine Learning and Windows 10 IoT enable computers to learn from data and experiences and makes devices smart. The Dynamics 365 for Connected realm Service enhances the service experience.

    Tie-ups with automakers

    While Microsoft is not using its IoT capabilities to develop its own connected cars, it is working with multiple players via its connected vehicle platform. This is a set of services built on the Microsoft Azure cloud designed to empower auto manufacturers to create custom connected driving experiences.

    “This is not an in-car operating system or a ‘finished product’ but a platform that aims to address five core scenarios that their partners hold told us are key priorities: predictive maintenance, improved in-car productivity, advanced navigation, customer insights and edifice autonomous driving capabilities,” Rege added.

    Besides this, Microsoft’s cloud ingests huge volumes of sensor and usage data from connected vehicles, thereby helping automakers apply that data in powerful ways.

    In India, the company already has partnership agreements with Ola Cabs, Tata Motors, Uno Minda and Tyre Express. Microsoft helped Ola develop its in-car entertainment experience, Ola Play, which is already being offered as a service.

    With Tata Motors, the company is offering drivers services such as shopping and route assist recommendations based on a driver’s profile, pre-emptive service alerts based on vehicle health data, firmware upgrades for cars, and live road and traffic information for customers.

    Enterprise IoT solutions firm Tyre Express has developed a tyre lifecycle management solution for fleet owners by using Microsoft’s Azure IoT service.

    Industrial IoT applications

    Microsoft is also offering its IoT services to enterprises through a solution called Microsoft Industrial Internet of things (IIoT).

    “Connected products, people and things produce terabytes of data every day that manufacturers can access and extract deep insights from to optimise commerce and manufacturing processes,” Rege said.

    Data from IIoT services can aid manufacturers identify recent revenue streams by developing high-value offerings focused on how products and customers interact in the real world.

    The company uses IIoT capabilities to monitor the attribute of drinking water, for smart city street lights and agriculture.

    Bengaluru-based TechSpan Engineering has implemented a monitoring system, which assesses water quality, built on the Azure IoT platform. It uses sensors provided by the Austrian firm s::can and their India confederate Aaxis Nano. Microsoft IoT data and s::can’s sensors provide measurements across 17 parameters, Rege explained.

    “We are also behind the Smart Street Lighting Project for Jaipur. The Jaipur Municipal Corporation (JMC) operates and maintains over 100,000 public street lights within the city,” he added.

    The project is expected to profit 1.65 million people through improved street lighting and will reduce greenhouse gas emissions by 36,750 metric tonnes/year. It will also result in $1 million per year in fiscal savings accrued to the government due to reduced energy consumption.

    For agriculture, Microsoft is working on a research project called FarmBeats, which comprises two broad areas—one involves collecting data from various sensors, cameras and drones, and the other consists of analysing that data.

    Microsoft has also provided machine learning capabilities to farm equipment-maker Escorts for its self-driving tractor.

    Besides the above, the company also provides IoT solutions in healthcare, transportation and retail.

    Microsoft competes with Cisco, Intel, Google and IBM in the IoT space among others.

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