The IoT world is a big world that everybody is talking about. IoT products nowadays come in different forms -- some are labelled as IoT, but in fact they represent only a small portion of what an IoT product really entails. A fully fledged IoT project not only requires programming and hardware expertise but also expertise on a broad range of domains from energy to smart home and even automotive. The purpose of this article is to highlight the significant differences among the Internet of Things (IoT) and Industrial Internet of Things (IIoT), and while walking through the listed considerations, the reader will have the chance to learn about their ecosystems and the particularities of their applications. Moreover, the gaps in the standardization of the technologies related to the IoT are presented along with the current initiatives from various institutions for mitigating these gaps.
US-based industrial manufacturers are slightly ahead of their Chinese counterparts in integrating artificial intelligence (AI) capabilities into their operations, even though both countries have a near-equal number of installed bases of AI-enabled devices, according to global tech market advisory firm ABI Research. Both countries are incentivized to develop approaches that encourage AI adoption in industrial manufacturing, but "the US has managed to achieve more momentum," according to Lian Jye Su, principal analyst. This is due to "acute challenges in manpower and rising cost of materials. So they need to adopt AI to make sure they can overcome these challenges." SEE: Deep learning: An insider's guide (free PDF) (TechRepublic) In China, manufacturers can still rely on "abundant human resources and government tax incentives to compete in the international market, keeping their margin healthy,'' Su added. The expensive US labor force has driven the industrial sector to enhance production efficiency and lower operational costs. This is prompting the major cloud service providers, smart manufacturing platform vendors, pure-play industrial AI platform and service providers, edge industrial AI gateway, and server and chipset vendors to partner to bring AI into industrial manufacturing, he explained. The partnerships are enabling an "end-to-end, cloud-to-edge solution to enhance operational efficiency, reduce bottlenecks and optimize resource consumption in factories," he said. AI is predominantly used in two areas: Overall efficiency enhancement and machine vision for inspection, production, and surveillance, according to Su. "For example, Instrumental is using images of printed circuit board to train their AI model in order to identify faults and low quality production on the smartphone production line,'' he said.
The global internet of things (IoT) in manufacturing market size was USD 27.76 Billion in 2018 and is projected to reach USD 136.83 billion by 2026, exhibiting a CAGR of 22.1% during the forecast period. The internet of things (IoT) in manufacturing comprises mechanical and electrical parts, advanced sensors, network connectivity architecture, controls, software applications, and smart devices that work together to collect and share real-time information between machines and humans. The internet of things (IoT) in manufacturing industry is gaining robust growth due to the rising adoption of AI (Artificial Intelligence) and other connected devices based on machine learning (M2M, M2P). Implementation of IoT technology in manufacturing industry is providing several organizations with new opportunities including digital transformations techniques and is enabling them to upgrade the current running operations by creating and tracking new business models. Furthermore, IoT solutions help in providing manufacturers a comprehensive vision to monitor complexities keep on arising at every intermediate point in the manufacturing process and assist in developing real-time adjustments.
China is ramping up its efforts to develop artificial intelligence in manufacturing to boost its productivity as well as create new momentum in the future market, an official at the Ministry of Industry and Information Technology said. The moves are part of the country's broad effort to integrate AI with the Made in China 2025 strategy, aiming to enhance efficiency and transform China into a global manufacturing powerhouse, according to Li Guanyu, deputy director of the information and software service division at the ministry. The ministry plans to release a white paper to drive the development of AI and its application in industries, Li said at the China International Big Data Industry Expo last month in Guiyang, Guizhou province. With its booming big data sector and mobile internet technologies, the nation has rapidly risen up the ranks of international AI research. The official said that now the country aims to use AI to drive the upgrade of its manufacturing, which is the backbone of the economy.
The fourth wave of the industrial revolution, known as Industry 4.0, connects industrial devices and permits organizations to use arranged information from IoT gadgets and PC controlled frameworks. Applying Artificial Intelligence (AI) and Machine Learning (ML) to this information makes fully automated smart factories, smart cities and more. Industry 4.0 is all about being digitally enabled and data driven, bringing together new technologies and compute services across edge and cloud assets to drive productivity, create new business models, and innovate faster. These technologies include everything from advanced analytics and AI to augmented reality, digital twins, and industrial IoT platforms, and, together serve the core needs of the manufacturing sector. IoT and Industrial IoT power mission-critical applications that require high reliability and unwavering quality.