Industrial parks are critical to urban economic growth. Yet, their development often encounters challenges stemming from imbalances between industrial requirements and urban services, underscoring the need for strategic planning and operations. This paper introduces IndustryScopeKG, a pioneering large-scale multi-modal, multi-level industrial park knowledge graph, which integrates diverse urban data including street views, corporate, socio-economic, and geospatial information, capturing the complex relationships and semantics within industrial parks. Alongside this, we present the IndustryScopeGPT framework, which leverages Large Language Models (LLMs) with Monte Carlo Tree Search to enhance tool-augmented reasoning and decision-making in Industrial Park Planning and Operation (IPPO). Our work significantly improves site recommendation and functional planning, demonstrating the potential of combining LLMs with structured datasets to advance industrial park management. This approach sets a new benchmark for intelligent IPPO research and lays a robust foundation for advancing urban industrial development. The dataset and related code are available at https://github.com/Tongji-KGLLM/IndustryScope.

To stay competitive, the Low- or Middle-Income Countries (LMICs) need to embrace Industry 4.0 and Logistics 4.0. This requires government-level interventions and policy-making to incentivize quality product solutions and drive innovation in traditionally resistant economic sectors. In this position paper, we support the establishment of Smart Industrial Parks (SIPs) with a focus on enhancing operational efficiencies and bringing together MSMEs and startups targeting niche clientele with innovative Industry 4.0 solutions. SIPs along with the phased deployment of well-planned robotic automation technologies shall enable bringing down India's untenable logistics costs. Toward the successful execution of SIPs, we are required to implement the efficient allocation of manufacturing resources and capabilities within SIPs. Thus, we emphasize the importance of efficient resource utilization, collaboration, and technology adoption in industrial parks to promote industrial development and economic growth. We advocate the use of a cloud-based cyber-physical system for real-time data access and analysis in SIPs. Such centralized cloud-based monitoring of factory floors, warehouses, and industrial units using IoT infrastructure shall improve decision-making, efficiency, and safety. Digital Twins (DTs), which are cyber-replicas of physical systems, could play a significant role in enabling simulation, optimization, and real-time monitoring of smart manufacturing and distributed manufacturing systems. However, there are several challenges involved in implementing DTs in distributed manufacturing systems, such as defining data schemas and collaboration protocols, ensuring interoperability, the need for effective authentication technology, distributed machine learning models, and scalability to manage multiple DTs.

With 5G, real-time computing will become a reality. The high speeds, high data throughput, and high number of connections that 5G enables will effectively erase the lag time between when data gets generated to when we can act on it. And, while self-driving vehicles might be the most visible new example of real-time processing most of us see, they are really only the tip of the iceberg, especially as private networks and network slicing roll out to bring the power of carrier-grade infrastructure to more locations and situations. IDC estimates that real-time data will grow by 50 times between 2000 and 2030 and constitute 30% of all data by then. Manufacturing will be one of the first places where a real-time data revolution takes place.

As technology continues to revolutionise the way we live and work beyond the pandemic, here are some early-stage companies innovating in the IoT space. The World Economic Forum (WEF) Technology Pioneers of 2021 represent a collection of 100 early to growth-stage companies identified as trailblazers working with new technologies and innovations. This year's list includes start-ups shaking up data and cybersecurity and blazing a trail in blockchain and digital assets. Here, we take a look at the IoT and smart city start-ups on the list, covering innovators that are finding advanced tech solutions to a burgeoning list of complex challenges in an increasingly digitised post-pandemic world. Founded by Andrea Thomaz and Vivian Chu in 2017, Diligent Robotics is a female-led early-stage company that makes AI-powered robot assistants for healthcare workers.

The vehicles still drive with a safety driver and a software operator. Optimus Ride, an MIT spinoff, has started operating its autonomous vehicles at Paradise Valley Estates in Fairfield, California. The shuttles, which have been carrying passengers for a couple of months now, follow deployments at the Seaport District in Boston, the Halley Rise mixed-use district in Reston, Virginia, and the Brooklyn Navy Yard in New York, a 300-acre industrial park. At the moment, the vehicles still drive with two people from the company on board, a safety driver and a software operator, but the goal of the company is to be fully driverless later this year. We caught up with the company recently -- check out the video below.

In a nondescript industrial park in Merrimack, New Hampshire, Jason Walker is putting the final touches on what he believes will become the iPod of working robots. Walker, 47, is co-founder of Waypoint Robotics, and the former lead quality and testing manager for the Roomba vacuuming robot. Waypoint, a tech startup about a year old, is housed in one cavernous room with high ceilings and a barebones office upfront filled with large, flat-screen monitors. Co-Founder and CEO Jason Walker is third from the left.Waypoints Robotics "We don't splurge on anything except screens and chairs," Walker says in the easy drawl of his native Kansas. Although he makes no claims to being another Steve Jobs, Walker does fervently believe that he and his small team are going to revolutionize robots in the same way Jobs revolutionized MP3 players.

Over the past year, more nations have come to realize the importance of artificial intelligence (AI) in shaping the economics of the future. With Russia, the United States, and the United Emirates all funding serious efforts to advance AI tech, China has established a three-year program to secure AI as a major economic driver by 2020. This is part of the nation's overarching plan to become an industry leader in AI by 2030. As a first step towards this goal, the Chinese government is preparing to build a technology park in Beijing dedicated to AI development research. The government is investing some $2.12 billion (13.8 billion yuan) to build the industrial park, located in west Beijing, according to state press agency Xinhua and as first reported by Reuters.

SEOUL – There was no evidence North Korea diverted wages paid to its workers by South Korean firms in a now-closed border industrial park to bankroll its weapons programs, an expert panel appointed by Seoul's Unification Ministry said Thursday. The investigation by the panel reversed the contention by the previous South Korean government that most of the cash that flowed into the jointly run Kaesong complex was diverted to North Korea's nuclear and missile programs. South Korea laid the claim when it pulled out of the joint venture in response to the North's launch of a long-range missile last year. But in July, two months after liberal President Moon Jae-in was elected, a South Korean government official said there was no hard evidence to back up the assertion. About 120 South Korean companies paid about double the $70 a month minimum wage in North Korea for each of the 55,000 workers hired in Kaesong.

The story first turned up in mid-May: Foxconn, Apple's favorite manufacturer, was replacing 60,000 of its workers with robots. Everyone from the BBC to Apple fan sites soon reported the ground-shifting news. There was just one problem: It was mostly false. Last weekend, a Foxconn spokesperson told Chinese media that the company hadn't laid off anyone, much less replaced them with automation. That part of the story came from overly enthusiastic bureaucrats in Kunshan, a manufacturing town keen to promote itself as a hub for innovation. The incident seemed like an apt metaphor.

Baidu Inc. is using its own trove of data to measure China's economy, devising new gauges that may paint a better picture than the government's. The country's leading search engine has begun using location and search information collected from its more than 600 million users to create indicators and indexes it says could shed light on what's happening with the world's second largest economy. Investors and analysts have long questioned the veracity and methodology of China's government-issued statistics. An example is jobless data, with an unemployment rate staying between 4 percent and 4.3 percent in every quarter since the end of 2002, through a domestic boom, the global financial crisis and now an economy growing at its slowest pace in 25 years. "The economy is slowing down but the unemployment rate published by the government remains steady about 4 percent," senior data scientist Wu Haishan said.