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Apeldoorn, Netherlands
1-10 Employees
2016
SignalZ is een IoT-platform voor het vertalen van sensordata naar relevante informatie voor procesverbetering en benodigde (preventieve) actie. SignalZ draait volledig in de cloud en werkt op desktop, tablet en mobiel. Dagelijks wordt SignalZ gebruikt voor het monitoren van fabrieken en sensoren over de hele wereld. Gebruik SignalZ om assets over de hele wereld te monitoren en te onderhouden. SignalZ beschikt over een geïntegreerde BI-omgeving waarmee u zelf dashboards kunt samenstellen. Wordt partner van SignalZ en verrijk uw domeinkennis met een state-of-the-art IoT platform waarmee u uw klanten kunt bedienen.Ook partner worden? Sluit uw assets aan op SignalZ en begin met het monitoren en optimaliseren van uw processen. Connecteer: Sensoren en machines van uiteenlopende merken kunnen aangesloten worden op het SignalZ platform.
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The IoT analytics platform.
... #smartindustry #iot #analytics ...
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IoT Analytics for Insurance
... SAS has the experience and expertise in advanced analytics, extensive analytics IP for insurance, and the ability to unify diverse, open source technology environments to help you reduce risk, ensure business continuity and accelerate time to value with IoT analytics solutions. ...
Herisau, Switzerland
1-10 Employees
2000
Seit 2001 machen wir im Team einzigartige Unternehmen mit innovativer Technologie, Know-how und Kreativität noch erfolgreicher. Als leidenschaftliche Brückenbauer zwischen IT und Business bieten wir ein umfassendes Portfolio an Dienstleistungen und Lösungen rund um das Thema der «digitalen Transformation» im Bereich der Prozessautomatisierung- und effizienz, an Schnittstellen und der Auswertung von Daten und bei der Erreichung Ihrer Zielgruppen mit Hilfe von Web Experience Plattformen. Gemeinsam mit clavis IT haben wir den digitalen Posteingang aufgebaut und verarbeiten die Anträge heute medienbruchfrei und ressourcenschonend. Wir haben mit clavis IT dieses innovative und zukunftsweisende Projekt als agiles Projekt durchgeführt. Dank dem massgeschneiderten Service konnten wir manuelle und fehleranfällige Arbeiten eliminieren und die Prozessdurchlaufzeiten reduzieren.
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IoT Analytics
... IoT Analytics - clavis IT ...
London, United Kingdom
1-10 Employees
2010
We are technology agnostic, working across multiple networking protocols. The Internet of Things is a network of devices that connect, send and receive data. IoT is a broad subject, not just M2M, but a technology collective. The Pervasive management team have been responsible for building one of the most innovative multi-service MSPs of late. With a desire to deliver outstanding versatility and value, Pervasive offers customers a view into Real World IoT. We work with leading suppliers of IoT Sensors from across the world, rigorously testing to ensure that they are fit for purpose. Our IoT platforms are built to scale and have been designed from the ground up to be compatible with many different network technologies, from LoRaWAN and Sigfox to NB-IoT, Cellular and Fixed. We offer both public cloud and private LPWAN networks that include global leaders such as Everynet and Loriot and M2M connectivity services via Comms365.
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Pervasive Solutions - IoT Analytics, Development and Sensors
... M2M / IoT Solution Provider offering Portal Development, licencing, IoT Analytics, Sensors. ...
Fredericia, Denmark
1-10 Employees
2019
Tricloud can help companies facilitate the transition to IIoT by providing deep technical knowledge and experience of planning, designing and implementing Industrial IoT solutions that can help realize new business opportunities such as:. Tricloud is a company which is closing the gap between classic OT (Industrial Automation) and new IT solutions based on cloud technology. At Tricloud, project management is a core business. Tricloud builds systems based on software from Microsoft that was designed with security in mind. We used Tricloud’s IoT consultancy services to better understand our maturity in IoT and plan specific improvements to our products. We are very impressed with Tricloud’s architectural and IoT knowledge. Tricloud learned our current state very quickly and delivered tangible recommendations clearly rooted in experience. Tricloud were flexible and enthusiastic throughout the work.
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AboutTricloud - Enabling Industrial IoT, Data analytics and AI
... AboutTricloud - Enabling Industrial IoT, Data analytics and ...
Hamburg, Germany
11-50 Employees
2014
We have conducted 550+ primary research interviews and built 40+ databases in the last years. Their team worked with us in a highly collaborative manner, and delivered a series of reports that were greatly appreciated by the digital leadership team and other key stakeholders in Marketing & Sales. IoT Analytics helped us conduct interviews with over 40 executives and experts across the IoT ecosystem. The subsequent analysis and IoT guidelines we developed together informed high level discussions with senior executives and public figures in Davos and will be a strong reference for our future work.
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Man and Machine in Industry 4.0 - IoT Analytics
... A BCG focus report, supported by IoT Analytics (Knud Lasse Lueth, Moritz Bolle) ...
United States
11-50 Employees
2018
Gyrus, with its experience in this space, attempts to make the transition to use ML/AI in businesses smooth, remunerating and rewarding. Gyrus built several building block technologies to make this transition seamless. At Gyrus, our main focus and concern is to develop and implement solutions that do not compromise on quality. Gyrus comprises a team of professionals with numerous years of experience in the field. Our Vision and Mission to be accomplished with values. Gyrus AI was incorporated in 2018 in the USA by technology industry veterans and serial entrepreneurs. The Gyrus AI team comprises 40+ Data Scientists and ML-AI Engineers in the in-house team and 100+ Software Engineers as an extended team. Gyrus technologies works with companies,governments,nonprofits and other organizations to address complex challenges and smart solutions on technology solutions world wide .
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IoT Analytics
... IoT Analytics ...
Milan, Italy
11-50 Employees
2007
With 10+ years experience Visup builds IoT / Analytics platforms that help Industrial and Data-centric companies to take on new challenges. We actively partner with companies for co-creating innovative data-centric products. I'm a manufacturer, I want to digitalise my plant. Check out Plant9 which offers out-of-the-box capabilities to increase production efficiency by leveraging on your industrial IoT analytics data. I'm a brand/OEM, I need an IoT platform for my customers.
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Visup | IoT Analytics Solutions for the Industry 4.0
... Visup | IoT Analytics Solutions for the Industry 4. ...
Seoul, South Korea
11-50 Employees
2003
Microsoft, Zalesia(Longview) 등 주요 벤더의 분석 부문 파트너이며, 국내 주요 대기업의 데이터엔지니어링 전문 협력업체입니다. AIoT 통합 환경/안전관리 플랫폼인 에코브리오(EcoBrio)를 개발하여 공급하고 있으며, 메타버스/데이터리터러시/인공지능 등의 기업 및 공공기관/지자체의 디지털전환 교육도 진행하고 있습니다. 유니즌은 Self-Service BI 기반의 모던 애널리틱스 분석 환경을 제공합니다. 고객사의 분석 요구사항에 적합한 솔루션과 컨설팅 서비스를 제공합니다. 유니즌에서 개발한 AIoT(사물지능인터넷) 기반의 통합 환경/안전관리 플랫폼인 “에코브리오(EcoBrio)”를 통해 다양한 분야의 AIoT 솔루션을 공급하고 있습니다. 관계사인 “메타포”를 통해 메타버스&AI의 교육과 컨설팅을 진행하고 있습니다. 2020년부터 “김해창업카페&메이커팩토리“와 협력하여 다양한 사업을 진행하고 있습니다.
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[카테고리:] IoT Analytics
... IoT Analytics – UNISON Co., Ltd. ...
Karachi Division, Pakistan
51-100 Employees
2015
Developing Business Solutions incorporating to deliver best Customer Experience. Track, analyze and visualize customer engagement behaviour, churn rate and more from our experienced product analytics team. Increase customer engagement by leveraging the most popular messaging app combined with a purpose-built chatbot. Pull data from IoT devices in realtime with industry leading tools and technologies for improved decision making. With our unique implementation strategy and smooth system delivery process, you won't have to worry about anything. We have offered companies a structured analysis of patient documentation with demographics, medical history, etc.
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Sudofy’s IoT Analytics
... Sudofy’s IoT Analytics ...
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Some interesting numbers and facts about the results you have just received for IoT Analytics
| Country with most fitting companies | United States |
| Amount of fitting manufacturers | 336 |
| Amount of suitable service providers | 299 |
| Average amount of employees | 11-50 |
| Oldest suiting company | 1976 |
| Youngest suiting company | 2019 |
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IoT Analytics refers to the systematic analysis of data generated by interconnected devices within the Internet of Things (IoT) framework. This complex process involves the collection, integration, and examination of vast volumes of data from various IoT devices, ranging from simple sensors to sophisticated industrial machines. The primary goal of IoT Analytics is to derive actionable insights from the raw data, enabling optimized operational efficiency, enhanced decision-making, and the development of new business models. By applying advanced analytics techniques, such as machine learning algorithms and predictive analytics, organizations can anticipate future trends, monitor real-time performance, and identify potential issues before they escalate. This proactive approach substantially reduces downtime and maintenance costs, improves customer satisfaction through personalized services, and drives innovation by uncovering hidden opportunities. As a cornerstone of digital transformation, IoT Analytics plays a pivotal role in various sectors, including manufacturing, healthcare, agriculture, and smart cities, by offering a data-driven pathway to achieving sustainable growth and competitive advantage. The impact of IoT Analytics extends beyond operational efficiencies, fostering a culture of continuous improvement and innovation that is essential for thriving in today's dynamic market landscape.
1. Enhanced Decision Making
IoT analytics provides real-time data analysis, enabling businesses to make informed decisions swiftly. Unlike traditional analytics, which may rely on outdated data, IoT analytics processes and interprets data as it's generated, ensuring decisions are based on the most current information available.
2. Improved Operational Efficiency
By analyzing data from IoT devices, companies can identify inefficiencies within their operations and take corrective action. This continuous stream of data allows for the optimization of processes, reduction of waste, and ultimately, a significant increase in overall operational efficiency compared to conventional methods.
3. Personalized Customer Experiences
IoT analytics enables the customization of products and services by understanding customer behavior and preferences in real-time. This level of personalization is challenging to achieve with alternative analytics options, making IoT analytics a superior choice for businesses aiming to enhance customer satisfaction and loyalty.
4. Proactive Maintenance and Predictive Analytics
Through the analysis of IoT data, organizations can predict potential failures before they occur and schedule maintenance proactively. This predictive capability reduces downtime and extends the lifespan of equipment, offering a significant advantage over reactive maintenance strategies that are common with other analytics approaches.
1. Data Integration Capabilities
Ensure the supplier can seamlessly integrate with a wide range of IoT devices and platforms, facilitating easy data collection and aggregation.
2. Real-time Analytics
Check for the ability to process and analyze data in real-time, enabling immediate insights and actions.
3. Scalability
The solution should be scalable to accommodate growing data volumes and complexity as your IoT ecosystem expands.
4. Security Measures
Evaluate the supplier's security protocols for data protection, especially for sensitive information transmitted by IoT devices.
5. Customization and Flexibility
Consider whether the analytics platform can be customized to meet specific business needs and how flexible it is to changes in requirements.
6. Support and Maintenance
Look for suppliers offering robust support and maintenance services to ensure the long-term reliability and performance of the analytics solution.
IoT analytics plays a pivotal role in predictive maintenance within the manufacturing industry. By analyzing data from sensors on equipment, businesses can predict when a machine is likely to fail or require maintenance. This insight allows for proactive upkeep, minimizing downtime and reducing costs associated with unexpected equipment failures. In the realm of supply chain management, IoT analytics offers unparalleled visibility and optimization opportunities. By tracking goods throughout the supply chain, companies can identify inefficiencies, predict delays, and optimize routes. This real-time data enables businesses to make informed decisions, improving operational efficiency and customer satisfaction. Energy management is another area where IoT analytics is transforming operations. Through the analysis of data from smart meters and sensors, businesses can identify patterns and areas of excessive energy use. This information is crucial for implementing energy-saving measures, reducing costs, and supporting sustainability initiatives. The healthcare sector benefits significantly from IoT analytics through enhanced patient monitoring. Wearable devices and embedded sensors provide continuous health data, allowing for personalized care plans and early detection of potential health issues. This proactive approach improves patient outcomes and can significantly reduce healthcare costs by preventing hospital readmissions. Each of these use cases demonstrates the versatility and impact of IoT analytics across various B2B sectors, highlighting its role in driving efficiency, reducing costs, and enhancing service delivery.
IoT Analytics, a burgeoning field that leverages the power of data collection and analysis from billions of connected devices, currently stands at a Technology Readiness Level (TRL) of approximately 7 to 8. This estimation is based on the integration and demonstration of IoT analytics in operational environments. The technical reasons underpinning this TRL include the advanced development of data processing algorithms, real-time analytics, and machine learning models that are now capable of handling vast quantities of unstructured data from diverse IoT devices. These technologies have been tested and validated in multiple real-world scenarios, showcasing their efficacy in predictive maintenance, energy management, and customer behavior analysis. However, it has not yet reached the ultimate TRL 9, primarily due to ongoing challenges such as ensuring data privacy, enhancing interoperability among different IoT systems, and scaling solutions to manage the exponential growth of IoT devices. The complexity of deploying IoT analytics across varied industries with different regulatory and compliance requirements also contributes to its current TRL, as it necessitates further refinement and customization of technologies to meet these diverse needs.
In the short-term, IoT Analytics is poised to see significant advancements in real-time data processing capabilities. With the increasing volume of data generated by IoT devices, the emphasis will be on enhancing edge computing technologies. This will allow for faster, more efficient processing of data closer to its source, reducing latency and improving decision-making processes. The integration of AI and machine learning for predictive analytics will also become more refined, providing actionable insights with greater accuracy. Looking into the mid-term developments, IoT Analytics will likely experience a surge in the adoption of advanced AI models, such as deep learning, to tackle more complex data analysis. This period will also witness the expansion of IoT analytics applications into new industries, including agriculture and manufacturing, driven by the need for precision and efficiency. The interoperability between different IoT systems and platforms will improve, facilitating a more seamless exchange of data and insights across various sectors. In the long-term, the field of IoT Analytics is expected to revolutionize with the advent of quantum computing. This will dramatically enhance the capacity to process and analyze vast datasets in fractions of the current time, opening new frontiers in predictive analytics. Additionally, the integration of IoT analytics with augmented reality (AR) and virtual reality (VR) technologies will provide immersive, real-time data visualization, transforming how insights are interpreted and acted upon. This era will mark a pinnacle in personalized and precise analytics, tailoring solutions to specific user needs and contexts.
Some interesting questions that has been asked about the results you have just received for IoT Analytics
What are related technologies to IoT Analytics?
Based on our calculations related technologies to IoT Analytics are Big Data, E-Health, Retail Tech, Artificial Intelligence & Machine Learning, E-Commerce
Which industries are mostly working on IoT Analytics?
The most represented industries which are working in IoT Analytics are Information Technology, Software, Internet Services, Data and Analytics, Hardware
How does ensun find these IoT Analytics Companies?
ensun uses an advanced search and ranking system capable of sifting through millions of companies and hundreds of millions of products and services to identify suitable matches. This is achieved by leveraging cutting-edge technologies, including Artificial Intelligence.
