Accurate power forecasting from renewable energy sources (RES) is crucial for integrating additional RES capacity into the power system and realizing sustainability goals. This work emphasizes the importance of integrating decentralized spatio-temporal data into forecasting models. However, decentralized data ownership presents a critical obstacle to the success of such spatio-temporal models, and incentive mechanisms to foster data-sharing need to be considered. The main contributions are a) a comparative analysis of the forecasting models, advocating for efficient and interpretable spline LASSO regression models, and b) a bidding mechanism within the data/analytics market to ensure fair compensation for data providers and enable both buyers and sellers to express their data price requirements. Furthermore, an incentive mechanism for time series forecasting is proposed, effectively incorporating price constraints and preventing redundant feature allocation. Results show significant accuracy improvements and potential monetary gains for data sellers. For wind power data, an average root mean squared error improvement of over 10% was achieved by comparing forecasts generated by the proposal with locally generated ones.

Kim Custeau, senior vice president of asset performance management and manufacturing execution systems at AVEVA, explains why performance intelligence will be critical in a post-pandemic industrial world that demands organisations develop a high level of agility, sustainability and resilience. Why is performance intelligence a critical focus today? The global big data and analytics market is growing at lightening pace and projected to be worth $274 billion by 2022. Staying ahead of the curve requires a new understanding of the scope and scale of industrial information to leverage that data effectively. Insight into industrial information from edge to enterprise reduces downtime, production costs and energy consumption, allowing organisations to optimise resources and drive sustainability.

It was soon evident that embracing digital technologies and using AI-driven analytics was the only way to remain buoyant and navigate the disruptions. Several companies worldwide have already transitioned to the work-from-home concept and have adapted to the modern distributed work ecosystem (See: How is digital transformation shaping the new future?). For CIOs, realigning priorities and accelerating enterprise innovations continue to be a roller-coaster experience amidst these unprecedented times. More and more enterprises are now leaning on data science and analytics to optimize business performance and drive growth. With virtual communication taking the center stage, there is a growing emphasis on implementing AI-based workforce analytics and business intelligence solutions to fast-track digital transformation and generate deeper operational insights to respond faster and steer the volatile economic landscape.

Today, when we look around, the technological advances in recent years have been immense. We can see driverless cars, hands-free devices that can turn on the lights, and robots working in factories, which prove that intelligent machines are possible. In the last four years in the Indian startup ecosystem, the terms that were used (overused rather) more than funding, valuation, and exit were artificial intelligence (AI) and machine learning (ML). We also saw investors readily putting in their money in startups that remotely used or claimed to use these emerging technologies. From deeptech, ecommerce, fintech, and conversational chatbots to mobility, foodtech, and healthcare, AI and ML have transformed most industry sectors today.

Rising number of contact centers and necessity for compliance and risk management across several verticals have led the companies to invent solutions in speech analytics which will aid companies to comprehend the changing necessities of customers. Several organizations functioning in diverse industrial domains have been evolving interests for the transcription and analyzing of customers and structural media and uptake rational decisions for the management of business and consumers with the help of speech and text intelligence. This is the main factor that is responsible for the growth of the speech analytics market and a protuberant driving factor in the growing demands for speech analytics in several industrial applications. This rising demand can also be accredited to the burdens on businesses for safeguarding their rational assets for improving agility and competence in business operations via the all-embracing insights quarried in the Voice of Customer (VoC). Speech analytics is used in sectors such as customer experience management, agent performance, business processes, compliance and risk management, and market intelligence.

Global Augmented Analytics Market was valued US$ 4.6Bn in 2018 and is expected to reach US$ 20.2Bn by 2026 at a CAGR of 19.98%. This report provides a detailed analysis of the market segment based on insurance type, sales channel and region. This report also focuses on the top players in North America, Europe, Asia Pacific, Middle East & Africa, and South America. The objective of the report is to present a comprehensive assessment of the market and contains thoughtful insights, facts, historical data, industry-validated market data and projections with a suitable set of assumptions and methodology. The report also helps in understanding the global augmented analytics market dynamics, structure by identifying and analysing the market segments and project the global market size.

Report Scope: The scope of the report includes, a general outlook of the analytics industry, with the scope limited to reports published during the year 2016, 2017 and 2018. This report covers only advanced analytics, artificial intelligence, and cognitive computing technologies. GNW The advanced analytics market covers the following solutions: software tools, integrated hardware appliances, and services. The advanced analytics market comprises applications for the following industries: banking and financial services, telecommunications and IT, healthcare, government and defense, transportation and logistics, and consumer goods and retail. The AI market covers machine learning, deep learning, and expert systems as these are direct derivatives of analytics.Cognitive computing market in this report covers machine learning and expert systems.

Rising number of contact centers and necessity for compliance and risk management across several verticals have led the companies to invent solutions in speech analytics which will aid companies to comprehend the changing necessities of customers. Several organizations functioning in diverse industrial domains have been evolving interests for the transcription and analyzing of customers and structural media and uptake rational decisions for the management of business and consumers with the help of speech and text intelligence. This is the main factor that is responsible for the growth of the speech analytics market and a protuberant driving factor in the growing demands for speech analytics in several industrial applications. This rising demand can also be accredited to the burdens on businesses for safeguarding their rational assets for improving agility and competence in business operations via the all-embracing insights quarried in the Voice of Customer (VoC). Speech analytics is used in sectors such as customer experience management, agent performance, business processes, compliance and risk management, and market intelligence.

The report "Video Analytics Market by Type (Software and Services), Application (Intrusion Management, Incident Detection, People/Crowd Counting, Traffic Monitoring), Deployment (On-Premises and Cloud), Vertical, and Region - Global Forecast to 2023", The global video analytics market size is expected to grow from USD 3.23 Billion in 2018 to USD 8.55 Billion by 2023, at a Compound Annual Growth Rate (CAGR) of 21.5% during the forecast period. The growth of the video analytics market is driven by many factors, such as disadvantages of manual video analysis, enterprises' demand for actionable insights from video data, government investments in emerging technologies to enhance public safety infrastructure, and falling prices of video surveillance equipment. With an increasing adoption rate of Internet of Things (IoT) and big data among enterprises, the video analytics market is expected to gain major traction during the forecast period. Early buyers will receive 10% customization on reports. The demand for video analytics software is being driven by its ability to be integrated with the originally deployed analog, IP, or megapixel cameras within establishments, thereby eliminating the need for the deployment of additional hardware.

This report on global Drone Analytics market is a detailed research study that helps provides answers and pertinent questions with respect to the emerging trends and growth opportunities in this particular industry. It helps identify each of the prominent barriers to growth, apart from identifying the trends within various application segments of the global market. The global Drone Analytics market size was 2.3 million US$ and it is expected to reach 5.6 million US$ by the end of 2025, with a CAGR of 10.4% during 2019-2025. Based on industry, the drone analytics market has been segmented into agriculture & forestry, construction, insurance, mining & quarrying, utility, telecommunication, oil & gas, transportation, scientific research, and others. The construction segment is projected to grow at the highest CAGR during the forecast period.