Connected Helmet Protects Workers: IBM IoT + ARM mbed in Action

Enterprise Iot

Article | May 11, 2023

In the wake of the COVID-19 pandemic, manufacturing is roaring back to life, and with it comes a renewed focus on Digital Transformation initiatives. The industry stands on the doorstep of its much-anticipated renaissance, and it’s clear that manufacturing leaders need to not only embrace but accelerate innovation while managing critical processes like increasing capacity while maintaining product quality. Effective collaboration will be key to doing both well, but it’s even more critical as workforces have gone and are still largely remote. As the virus swept the globe, it became apparent quickly that there would be winners and losers. Many manufacturers were caught off-guard, so to speak. Before manufacturing’s aforementioned reckoning, the industry had already been notorious for its slow adoption of the digital, data-centric mindset that has transformed other industries.

Industrial IoT, IoT Security

Article | July 11, 2023

Edge computing enables the IoT to move intelligence out to the edge. If organizations have a lot of data and need to use it, they should do so in end-to-end paths, environments with lots of sensors, or environments where a lot of data is generated at the edge, thanks to the Internet of Things (IoT) and edge data sensing. Additionally, traditional methodologies fall short of the necessary standards when dealing with real-time information and the growing amount of unstructured data, which includes a sensor and IoT data. For management, power concerns, analytics, real-time needs, and other IoT situations, speed and high-speed data are essential elements. This enables edge computing to handle data. The Internet of Things (IoT) benefits from having compute capacity close to the location of a physical device or data source. IoT device data needs to be processed at the edge rather than traveling back to a central site before that analysis can be done in order to react quickly or prevent concerns. For the data processing and storage requirements of IoT devices, edge computing serves as a local source. Benefits of Using IoT and Edge Together The connection between IoT devices and the main IT networks has less latency. Greater operational efficiency and quicker response times. Network bandwidth improvement. When a network connection is lost, the system continues to run offline. Utilizing analytics algorithms and machine learning, local data processing, aggregation, and quick decision-making are possible. Industrial IoT, often known as IIoT, is the application of IoT in an industrial setting, such as factory machinery. Consider the lifespan of the large, factory-used machinery. Equipment may be stressed differently over time depending on the user, and malfunctions are a regular aspect of operations. The parts of the machinery that are most prone to damage or misuse can be equipped with IoT sensors. Predictive maintenance can be performed using the data from these sensors, cutting down on overall downtime. Because IoT devices can be used as Edge Computing, the line between IoT and Edge Computing can occasionally be razor-thin. However, the most significant difference is the ability not only to compute data locally (in real-time) but also to sync that data to a centralized server at a time when it is safe—and feasible—to send. IoT and edge computing are both here to stay since they fulfill crucial societal and commercial needs.

IoT Security

Article | October 11, 2023

Artificial intelligence is becoming increasingly crucial in IoT applications and deployments. Over the past two years, investments and acquisitions in firms that combine AI and IoT have increased. IoT platform software from top suppliers now includes integrated AI features, including machine learning-based analytics. When artificial intelligence is linked with the internet of things, we get Artificial Intelligence of Things (AIoT). The prime motive for combining AI and IoT is that, while IoT devices are used to gather data and send it to a cloud or other location where it can be stored using the internet, AI, which is regarded as the brain of AIoT, is what actually aids in decision-making and simulates how machines would act or react. Other artificial intelligence (AI) tools, such as speech recognition and computer vision, can assist reveal patterns in data that previously needed human evaluation. AI applications for IoT-enabled companies help them avoid several issues: Preventing expensive unplanned downtime Predictive maintenance can lessen the adverse economic effects of unplanned downtime by employing analytics to anticipate equipment failure and arrange orderly maintenance processes. In order to predict equipment failure, machine learning enables the discovery of patterns in the continuous streams of data produced by today's technology. Operational efficiency advancement IoT with AI capabilities can also increase operational effectiveness. By processing continuous data streams to find patterns invisible to the human eye and not visible on simple gauges, machine learning can predict operating conditions and identify parameters that need to be adjusted immediately to maintain ideal results, just as it can predict equipment failure. Improved risk management IoT and AI-powered applications enable businesses to automate for quick reaction, better analyze and predict a range of hazards, and control worker safety, financial loss, and cyber threats. Finding an IoT system that does not incorporate AI could soon be uncommon. With the help of AI, organizations can truly enhance the potential IoT and effectively put it into use for improving the overall functioning.

Article | April 27, 2020

Manufacturing industry or the Industrial Internet of Things has been one of the driving verticals for development of 5G technologies. Wide 5G deployement for Industrial IoT has long been in the pipeline but we might expect it to be a reality very soon. The true success of 5G depends on the verticals as trends suggest that that Industrial IoT alone will triple the number of needed base stations globally. And many verticals will need efficient wireless connectivity to become successful. 5G has features that are specifically designed to address the needs of vertical sectors, such as network slicing and URLLC. The ultra-reliable low latency communications and massive machine type communications required by the IIoT will soon be realized. Table of Contents: How Will 5G Impact Industrial IoT? 5G Accelerations for IIoT Industrial 5G How Will 5G Benefit Industrial IoT? IoT is a B2B application and users just want to get actionable data from their sensors and not worry about whether it’s old data or unreliable data. I think 5G changes this dynamic significantly over the long term by standardizing and simplifying the experience and interactions, and possibly engaging more of the industry to help solve IoT’s problems but also improve the total experience. - Anshel Sag, analyst at Moor Insights & Strategy • Data-Transfer Speeds Any IoT is said to be commercially successful depending on how fast it can set up communications with other IoT devices, software based websites or applications, phones, and tablets. 5G promises exactly all of this with significant increase in transfer speeds. 5G is 10x faster than its LTE counterparts and allows IoT devices to communicate and share data faster than ever. All IoT devices will benefit from the faster speed of 5G with reduced lag and improved sending and receiving of data and notifications between connected devices. • Greater Network Reliability 5G networks also offer more reliable and stable connection which is extremely important for any IoT including devices like locks, security cameras and monitoring systems that depend on real-time updates. With reliable connectivity consumers will be the greater beneficiary. It is however, imperative for manufactures to trust and invest in 5G compatible devices to reap the benefits of high-speed connectivity, very low latency, and a greater coverage that will arrive with the next generation network. READ MORE:How Will the Emergence of 5G Affect Federated Learning? 5G Accelerations for IIoT • Diversity in Industrial IoT The opportunities that industrial IoT bring with is varied and its used cases span the spectrum from indoor to outdoor, less demanding to mission-critical, data rate from dozens of bps to gbps, device motion from fixed to mobility, and power source from button battery to high voltage. Predictive maintenance, smart metering, asset tracking, and fleet management are some of the commonly known opportunities for IIoT, which be extended further by 5G through continued diversity and expansion. • 5G Inspires Untapped Frontiers Industrial IoT application areas such as mobile robot control in production automation and autonomous vehicles in open pit mining require wide mobility, low latency and mission-critical reliability. They rely on wireless access at 50ms to 1ms latency and service reliability from 5 nines to 6 nines. Though 4G/LTE has attempted to address these areas of IIoT application it has failed due to unsatisfactory performance. With ultra-reliable and low latency connection, 5G will take industrial IoT to unconquered spaces. • Managing the Enterprise 5G Network Typically, enterprise IT is responding to the business demand from Operational Technology (OT) and mandates security, integration, visibility, control, and compatibility. In this scenario, 5G is not about “what,” but about “how”. IT needs to consider the right approach to bring 5G to the enterprise and decide whether to co-manage with the service provider (SP) or self-manage. The experience of IT in managing Industrial Ethernet and Wi-Fi may not hold when it comes to 5G. IT will likely require OT’s partnership to address complexity, security, integration, and other new challenges that 5G presents. Industrial 5G The potential for industrial 5G huge as it enables whole new business models. Industrial IoT has a core requirement of the ability to connect sensors, devices, software applications, production process, workers and consumers. The connectivity requires to be seamless vertical and horizontal integrations of all layers of automation pyramids that increases operational efficiency of the plant floor and the supply chain by optimal use of data, information and analytics. This can be improved by five key elements: • Improved Connectivity • Availability • Low Latency • Flexibility • Speed Industrial 5G will impact these areas of the manufacturing industry to guide the success of Industrial IoT. Industrial 5G will play a key role in helping industrial users achieve the goals of Industrial IoT. 5G offers wireless communications services with reduced latency, increased connection density, and improved flexibility compared to the current 4G generation. 5G technology has a theoretical downlink peak speed of 20 Gbps (gigabits per second), which is about 20 times faster than the current generation. The key is to start building IoT devices with broadly adopted operating systems, built-in security all the way down to the silicon, verifiable and updatable firmware, and mainstream application development tooling. - Anshel Sag, analyst at Moor Insights & Strategy The push and pull in achieving 5G success in IoT will be there until technology providers and end users work together to set up a consensus on standardization. The success will also depend on best-of-breed approach allowing the introduction of new technology over the lifecycle. Software and system integration will also be important attributes to a successful 5G deployment. READ MORE:How Will IoT Revolutionize Pharmaceutical Manufacturing?