Call for Proposals: The ESA Copernicus 2.0 Challenge

The ESA Copernicus 2.0 Challenge is looking for solutions that reflect the upcoming “golden era” in Earth Observation by demonstrating how new trends in EO can work together with the traditional EO satellites. Copernicus 2.0 will rely on a combination of large and traditional satellites with SmallSats. Constellations of NanoSats, HAPS (High Altitude Platform Stations) and drones are certain to become important contributors of EO data, complementing the more traditional fleet of the Copernicus Sentinels and Contributing Missions
Application Deadline in 3 months

Hula Hoop Industry 2019 Global Market Share, Growth, Manufacturers, Size, Segments and 2025 Forecast

New research report on Hula Hoop Market 2019 Global Industry includes detailed analysis market trends, innovations, growth, and forecast 2025. The report presents market main objective of sharing this market research report is to provide an in-depth analysis of the market share, historical data, profitability, opportunities, sales, and revenue distribution. The research study offers current market size, manufacturers’ analysis and segmentation of Hula Hoop across the globe.
7 days ago

Augmented Virtual Reality: Combining Crowd Sensing and Social Data Mining with Large-Scale Simulation Using Mobile Agents for Future Smart Cities

Augmented reality is well known for extending the real world by adding computer-generated perceptual information and overlaid sensory information. In contrast, simulation worlds are commonly closed and rely on artificial sensory information generated by the simulator program or using data collected off-line. In this work, a new simulation paradigm is introduced, providing augmented virtuality by integrating crowd sensing and social data mining in simulation worlds by using mobile agents.

Call for Proposals: Airbus Sobloo Multi-Data Challenge

Airbus Defence and Space together with sobloo are looking for solutions that use both Copernicus and Airbus Earth Observation data to deliver new services and/or applications that provide insight and have impact on areas like Natural Resources Consumption, Agriculture, Forestry, Maritime, Defence & Security and Smart Cities. Participants with solutions for other markets are also eligible to enter the Challenge. Solutions should be technically operational, compatible with Airbus and Copernicus EO data and provide valuable information to the end users.
Application Deadline in 3 months

Methyl Cellulose Industry 2019: Global Market Strategy, Trends, Outlook, Size, Share, Demand, Development Analysis and Forecast 2025

Worldwide Methyl Cellulose Industry 2019 Market Research Report explores an in-depth insight of Methyl Cellulose Market covering all important parameters including market trends, challenges, opportunities, key manufacturers and competitive analysis. Methyl Cellulose Market report includes historic data, Future Growth, and this factor which is valuable & supportive to the business. It gives the top to bottom analysis of market Size, Share, Opportunity, analysis and forecast to 2025. It vast repository provides analytical overview of market that will help to new and existing players to take important decision.

Detecting Indicators for Startup Business Success: Sentiment Analysis Using Text Data Mining

The main aim of this study is to identify the key factors in User Generated Content (UGC) on the Twitter social network for the creation of successful startups, as well as to identify factors for sustainable startups and business models. New technologies were used in the proposed research methodology to identify the key factors for the success of startup projects.

Call for proposals: The 2019 Call for Code Global Challenge

The Call for Code Global Initiative rallies developers to create practical, effective, and high-quality applications based on cloud, data, and artificial intelligence that can have an immediate and lasting impact on humanitarian issues.
Application Deadline in 4 months

Call for Applications: Google/SAP Circular Economy 2030 Contest for Social Entrepreneurs

Applicants are encouraged to submit proposals for revenue-generating ideas using data analytics and machine learning that work toward creating a circular economy in which consumption and emissions are minimized through recycling, reuse, refurbishing, and repair.
Applications are closed

Artificial Intelligence Drives Disruption in the Analytics Space, Finds Frost & Sullivan

The availability of ever-increasing amounts of structured and unstructured data, along with higher, cheaper and faster computing power, has been essential for the development of advanced analytics. The Internet of Things (IoT) has also boosted the development of the streaming analytics market through sensor-driven, real-time insights into consumer behavior.
a year ago

JDA Software collaborates with MIT to advance research in intelligent supply chains

It is more critical than ever to infuse innovation into every aspect of the supply chain, as edge technologies such as the Internet of Things (IoT) and artificial intelligence (AI) are essential to digitally transforming supply chains.
a year ago

New Predictive Analytics Platform analyzes Big Data to answer plain-language business queries in minutes instead of months

Users of the new platform upload data about customers or other individuals, such as records of mobile phone calls, credit card purchases, or web activity. They use Endor’s “query-builder” wizard to ask questions, such as “Where should we open our next store?” or “Who is likely to try product X?” Using the questions, the platform identifies patterns of previous behavior among the data and uses social physics models to predict future behavior. The platform can also analyze fully encrypted data-streams, allowing customers such as banks or credit card operators to maintain data privacy.
a year ago

Reinforcement Learning for Predictive Analytics in Smart Cities

We discuss an intelligent process for query assignments that adopts Machine Learning (ML). We adopt two learning schemes, i.e., Reinforcement Learning (RL) and clustering. We report on the comparison of the two schemes and elaborate on their combination. Our aim is to provide an efficient framework to support the decision making of the QC that should swiftly select the appropriate processor for each query.
a year ago

Predictive Analytics Improve Emergency Operations

The WWW is rich with data feeds - social media, internet of things (IoT), surveillance, primary surveys, biometrics, spatial imagery - however, we consume a very tiny fraction of this massive information mine to determine outcomes.
2 years ago

Reinforcement Machine Learning for Predictive Analytics in Smart Cities

In this paper, we define the concept of a Query Controller ( QC ) that receives queries for analytics and assigns each of them to a processor placed in front of each data partition. We discuss an intelligent process for query assignments that adopts Machine Learning (ML). We adopt two learning schemes, i.e., Reinforcement Learning (RL) and clustering.
2 years ago

Find & Pay uses Big Data, Predictive Analytics and Machine Learning to create Accurate Parking Probability Map

Find & Pay, uses big data, predictive analytics and machine learning to reduce the time it takes to find parking in congested cities by up to 50 per cent, reducing stress for motorists and the congestion and emissions associated with city parking today.
2 years ago

Next Evolution in IoT Will Be Sentient Tools and Cognition or Predictive Computing

In Europe, IoT connections are set to exceed 9 billion by 2021. Dedicated venture funds for IoT development will help create an ecosystem that is conducive to the growth of startups in the region.
2 years ago

Huawei and GE Release Industrial Cloud-based Predictive Maintenance Solution

The new solution seamlessly integrates Huawei's Edge Computing IoT (EC-IoT) with GE's Industrial Internet cloud platform Predix to enable rapid end-to-end connectivity between industrial assets and cloud applications, allowing real-time machine health monitoring, data analysis and perception, and smart maintenance decision-making.
2 years ago

World Bank Group Launches New Open Data and Analytics Energy Platform

Key energy sector data will now be easily accessible in one place and at no cost on the new and growing ENERGYDATA.INFO, an open data and analytics platform the World Bank Group and partner organizations launched today at the Sustainable Energy for All Forum.
2 years ago

An IoT Based Predictive Connected Car Maintenance Approach

This paper discusses one such use case, which can be implemented by the automobile industry, using technological advancements in the areas of IoT and Analytics. ‘Connected Car’ is a terminology, often associated with cars and other passenger vehicles, which are capable of internet connectivity and sharing of various kinds of data with backend applications.
2 years ago

NEXTracker™ Launches the Industry's 1st Solar Tracker Plus Storage Solution based on NEXTracker protocol, Machine Learning and Predictive Analytics Capability

NEXTracker announced it has launched an innovative solar plus energy-storage solution for U.S. and international markets. NX Fusion Plus integrates the latest, best-in-class solar tracker, battery, inverter, and software to deliver better return on investment to owners of solar power plants. By incorporating battery storage technology into its product, NEXTracker is further increasing the energy output and duration of solar power plants, just as tracking technology did for fixed-tilt solar applications.
2 years ago

Predictive and Control Capabilities through IoT Rapidly Expand Global Growth Opportunities for Sensors

Smart sensors are now evolving to be prognostic/ predictive. With up-gradation of contact, non-contact technologies and evolution of hybrid technologies, sensors are proactively enabling new applications. Sensors are at the forefront of digital transformation across diverse industrial markets.
2 years ago

Predictive Analytics Using Soft Computing: A Case Study on Forecasting For Indian Automobile Industry

This paper aims at providing a proposed neural network solution that can be used to predict the future sales on the base of historical data using Back Propagation algorithm. Especially we aim at finding which automobile company will be on a high scale of sales as per the customer’s capacity and desire. This forecasting helps firms to take strategic decisions to achieve their goals.
2 years ago

Frost & Sullivan: Significant opportunities for Big Data, remote monitoring and predictive analytics providers in Australian AgriTech Market

The Australian precision agriculture market accounted for approximately 7.2 percent of the global market share in 2015 and is forecast to increase its share over the next 5 years. Adoption of remote monitoring, Big Data, variable rate technology and farm management software will also drive the precision agriculture market.
2 years ago

Data Analytics for Smart Parking Applications

We consider real-life smart parking systems where parking lot occupancy data are collected from field sensor devices and sent to backend servers for further processing and usage for applications. Our objective is to make these data useful to end users, such as parking managers, and, ultimately, to citizens. To this end, we concoct and validate an automated classification algorithm
2 years ago

Plenarium Delivers Predictive Analytics that Accelerate Human Capital

Plenarium Inc. announces the formation and launch of a new company delivering predictive talent and other advanced analytics solutions, resulting in measurable "return on talent." Plenarium has assembled a team of executives and scientists with extensive experience in behavioral science, technology, and business, as well as experts in entrepreneurial and operational management.
3 years ago

A*STAR Researchers developed a sensor node processor using ultra-low power consumption for IoT devices

IoT applications range from biomedical signal processing to uses in vehicle-status monitoring and environmental sensing. Most IoT devices are tiny in size, which means that they typically consume only a small amount of power. This is particularly challenging for processors that sample the information from sensors and analyze the data, as their power demands, in contrast, are intense, explains Xin Liu and Jun Zhou from the research team.
3 years ago

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