At least four people were killed in Russia's overnight bombing of Ukraine's second-largest city of Kharkiv, Mayor Ihor Terekhov said on the Telegram messaging app. Kharkiv lies about 30km (18 miles) from the Russian border and has been repeatedly targeted by Russian aerial attacks. An earlier attack on Kharkiv injured six people and destroyed much of the Derzhprom building, one of the most celebrated landmarks in the city, dating from the 1920s. Two people were injured and a residential building caught fire in Solomianskyi, a district in the Ukrainian capital, Kyiv, after a Russian drone attack, Mayor Vitali Klitschko said. One person was killed and 11 wounded after a Russian missile struck a three-storey residential building in Kryvyi Rih, Ukrainian President Volodymyr Zelenskyy's hometown.

Short-term industrial enterprises power system forecasting is an important issue for both load control and machine protection. Scientists focus on load forecasting but ignore other valuable electric-meters which should provide guidance of power system protection. We propose a new framework, multi-variable adversarial time-series forecasting model, which regularizes Long Short-term Memory (LSTM) models via an adversarial process. The novel model forecasts all variables (may in different type, such as continue variables, category variables, etc.) in power system at the same time and helps trade-off process between forecasting accuracy of single variable and variable-variable relations. Experiments demonstrate the potential of the framework through qualitative and quantitative evaluation of the generated samples. The predict results of electricity consumption of industrial enterprises by multi-variable adversarial time-series forecasting model show that the proposed approach is able to achieve better prediction accuracy. We also applied this model to real industrial enterprises power system data we gathered from several large industrial enterprises via advanced power monitors, and got impressed forecasting results.

Video captures the moment and aftermath of what appears to be a drone, allegedly of Ukrainian origin, striking Russian drone production facility. Russian officials claimed that only a worker's dormitory was hit. A Ukrainian "plane-type UAV" on Tuesday struck a Russian weapons plant that allegedly assembled drones, causing an incredible fireball after impact. "This morning, the republic's industrial enterprises in Yelabuga and Nizhnekamsk were attacked by drones," Rustam Minnikhanov, the leader of Russia's autonomous Republic of Tatarstan, said in a post on his Telegram channel. "There is no serious damage, the technological process of the enterprises was not disrupted," Minnikhanov added.

The governor of Russia's Bryansk region accused Ukraine of using cluster munitions against a Russian village near the Ukrainian border. Several houses in the village of Klimovo were damaged, although no casualties were reported. The Ukrainian Air Force said it destroyed 29 of 31 drones and one cruise missile launched by Russia, mostly towards the regions of Mykolaiv and Dnipropetrovsk, during overnight attacks that lasted more than three hours. Falling debris from destroyed Russian drones caused fires in Dnipro and in an industrial enterprise in Pavlograd, two cities in Ukraine's eastern Dnipropetrovsk region. Firefighters managed to extinguish both fires and there were not initial reports regarding victims.

When digital transformation is discussed, technology is usually not far behind. Whether it's Internet of Things (IoT), cloud, or artificial intelligence (just to name a few), tech is changing how organizations around the world are doing business. While there's no question that technology goes hand-in-hand with digital transformation, there are other essential considerations that must come first in a digital transformation strategy. These include identifying value-driven business outcomes and developing a culture of change and collaboration. In our State of Industrial Digital Transformation report, our research analysts describe DX technologies as "levers or tools to support business value-oriented initiatives."

Soracom, Inc., a global provider of advanced Internet of Things (IoT) connectivity, announced that ThingsMatrix, an experienced IoT solutions provider that offers full turnkey services, has joined the Soracom Partner Space – a growing ecosystem for building and scaling IoT applications to advance asset monitoring for industrial enterprises. "Soracom is committed to democratizing the technologies that help IoT innovators accelerate speed to market and ensure success at scale" ThingsMatrix offers a robust cloud-based platform designed to simplify IoT development and deployment processes for enterprises. The company's turnkey solution includes three versatile components – device, platform and cellular connectivity – enabling a full range of functionality from simple tasks to complex actions. With custom, off-the-shelf, or bring your own devices available to track and monitor assets globally, ThingsMatrix offers the speed, security and scalability today's industrial enterprises need to navigate the complexities of IoT, thus reducing risk and accelerating time-to-value. AI and ML News: Why SMBs Shouldn't Be Afraid of Artificial Intelligence (AI) "ThingsMatrix's versatile turnkey device solutions and service platform paired with Soracom's reliable and advanced IoT capabilities is a major step forward for total asset management," said Tom Burton, ThingsMatrix's president of global sales.

Artificial intelligence (AI) has evolved from hype to reality over the past few years. Algorithmic advances in machine learning and deep learning, significant increases in computing power and storage, and huge amounts of data generated by digital transformation efforts make AI a game-changer across all industries.8 AI has the potential to radically improve business processes with, for instance, real-time quality prediction in manufacturing, and to enable new business models, such as connected car services and self-optimizing machines. Traditional industries, such as manufacturing, machine building, and automotive, are facing a fundamental change: from the production of physical goods to the delivery of AI-enhanced processes and services as part of Industry 4.0.25 This paper focuses on AI for industrial enterprises with a special emphasis on machine learning and data mining. Despite the great potential of AI and the large investments in AI technologies undertaken by industrial enterprises, AI has not yet delivered on the promises in industry practice. The core business of industrial enterprises is not yet AI-enhanced. AI solutions instead constitute islands for isolated cases--such as the optimization of selected machines in the factory--with varying success. According to current industry surveys, data issues constitute the main reasons for the insufficient adoption of AI in industrial enterprises.27,35 In general, it is nothing new that data preparation and data quality are key for AI and data analytics, as there is no AI without data. This has been an issue since the early days of business intelligence (BI) and data warehousing.3 However, the manifold data challenges of AI in industrial enterprises go far beyond detecting and repairing dirty data. This article profoundly investigates these challenges and rests on our practical real-world experiences with the AI enablement of a large industrial enterprise--a globally active manufacturer.

Industrial enterprises are increasingly turning to edge computing for the shorter latencies, robust security, responsive data collection, and lower costs it offers organizations, according to a new study from Frost & Sullivan. The report looks ahead to 2024 and described edge computing as a "foundational technology" that 90% of industrial enterprises will be using by 2022. According to Frost & Sullivan analysts, edge computing will be key as industrial environments become more hyper-connected in the coming years with a litany of autonomous assets, remote asset monitoring, data extraction from stranded assets, autonomous robotics, autonomous vehicles, and smart factories. The study estimates that the multi-access edge computing market may grow at a compound annual growth rate of 157.4%; it brought in revenue of $64.1 million in 2019 and is slated to bring in $7.23 billion by 2024, according to Frost & Sullivan analysts. "The recent launch of the 5G technology coupled with multi-access edge computing brings computing power close to customers and also allows the emergence of new applications and experiences for them," said Renato Pasquini, information & communication technologies research director at Frost & Sullivan.

LiveWorx is a one-of-its-kind premier technology industry event held at the Boston Convention and Exhibition Center (BCEC)and showcases the latest innovation, emerging technologies, tools, experiences, tech demos transforming today's digital industrial enterprise to the next level. LiveWorx'19 attracted close to 6,359 attendees (and 3,233 via live streaming) from 74 countries. Keynote tracks, workshops, and tech demos focused on "Digital Engineering", which included product design and product lifecycle management, and "Industry 4.0", which included connected smart enterprise assets/products transmitting valuable data at the edge or to the cloud to generate real-time analytics using AI and visualize the resulting actionable insights using Digital Dashboards or Augmented Reality. PTC with its comprehensive portfolio from CAD for design (PTC CREO) to PLM (PTC Windchill) for manufacturing to IoT (PTC ThingWorx) and AR (PTC Vuforia) for connected assets monitoring to data visualization respectively and key partnerships with Microsoft, Rockwell Automation, Vodafone Business and other is empowering this organization to transform digitally accelerating the goal of saving money / making money and also drive greater customer satisfaction. PTC had a number of customers and partners showcasing demos at LiveWorx, however, most of them showcased the power of IoT (streaming data) from machines AR (data and insights visualization) in the industrial IoT setting.

Assembly robots that build things on their own without having to be programmed for it. Trains or wind turbines that request maintenance work on the basis of operating data and artificial intelligence (AI), which can predict their behavior better than the engineers who developed and built them. This development is an opportunity if we come up with ideas for shaping it in a positive way and turning AI into a job engine. There is no question that the ascendancy of AI will further change the world of work. Leading market research institutions are unanimous in their estimation that up to 50 percent of most activities can be automated.