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Unlocking the power of AI: transforming IoT data into actionable insights

AI empowers IoT - image Softweb Solutions

02 June 2023

Sonya Weiser
Image: Softweb Solutions


Harnessing the potential of Internet of Things data to drive innovation and efficiency through Artificial Intelligence.

Last month I attended the annual Internet of Things (IoT) conference and expo, which was held in Sydney’s convention centre. It was interesting to hear how IoT data can be effectively used, gathering large amounts of data for analysis and interpretation. The event included both keynote conference speakers and a large expo of IoT providers, who I’ve listed at the end of this blog post.

image: IoT Hub
image: IoT Hub

I heard some interesting speakers on how IoT is being used in a range of industries such as gas, manufacturing, construction and farming. The keynote speaker I found to be the most inspirational was Barry Irvin AM, the executive chairman of Bega, who spoke about harnessing the power of IoT to transform the entire Bega Valley into a circular economy. More on that later in my blog post!

Now that AI has become topical and part of the public consciousness due to the popularity of Chatty G (Open AI’s ChatGPT), we’re looking for effective ways to use AI in business. Following the conference, I’ve been thinking about why it’s taken so long for IoT solutions to be adopted. It’s been around for a long time, but it’s been a technology looking for a solution. The opportunity for adoption of IoT now is the massive amounts of data collected by IoT sensors, which when combined with AI can be used to extract valuable insights and drive informed decision making.

Generative AI algorithms such as Chatty G make it easy to understand and interact with AI, as they use natural language processing. But the answers from AI are only as good as the data that’s used to train it, the age-old dilemma of garbage in = garbage out. There’s a lot of talk at the moment about the dangers of AI, rightly pointing out major limitations of generative AI answers which can be entirely wrong or simply misleading, and might be taken for fact from people blindly trusting technology.

The optimal use of AI is within a controlled environment, where you know that the data used to train the AI is accurate. IoT sensor data is perfect for AI input, training the AI with massive amounts of data that is within your control.

Here are just a few of the ways AI can leverage IoT data:

  1. Data Analysis and Pattern Recognition: AI algorithms can analyse large volumes of IoT sensor data to identify patterns, trends, and anomalies that humans may overlook. By detecting correlations and abnormalities, AI can uncover hidden insights and provide valuable context for decision-making.
  2. Predictive Analytics: AI can utilise historical IoT sensor data to develop predictive models. These models can forecast future events, such as equipment failures, customer behaviour, or supply chain disruptions. By anticipating potential issues, businesses can pro-actively take corrective actions and optimise their operations.
  3. Real-time Monitoring and Alerts: AI-powered systems can continuously monitor IoT sensor data in real-time. By setting up thresholds and rules, AI can trigger alerts when specific conditions are met. For example, in a manufacturing setting, AI can detect deviations from optimal performance levels or safety thresholds and immediately notify relevant stakeholders for prompt action.
  4. Intelligent Automation: By integrating AI with IoT devices, automation can be enhanced significantly. AI algorithms can analyse sensor data to make autonomous decisions and trigger actions without human intervention. This enables processes to be streamlined, optimised, and made more efficient.
  5. Enhanced Personalisation: AI can leverage IoT data to deliver personalised experiences to users. By analysing data from sensors embedded in various devices, AI can understand user preferences, behaviour patterns, and context. This enables personalised recommendations, targeted advertisements, and tailored user experiences.
  6. Energy Efficiency and Resource Optimisation: AI algorithms can optimise energy consumption and resource utilisation based on IoT sensor data. By analysing data from smart meters, environmental sensors, or energy usage patterns, AI can identify energy-saving opportunities, suggest optimisations, and help reduce waste.
  7. Security and Anomaly Detection: AI can enhance security measures by analysing IoT data for abnormal patterns or potential threats. By continuously monitoring sensor data and comparing it against established baselines, AI can detect security breaches, unauthorised access attempts, or suspicious behaviour, enabling prompt response and mitigation.

Overall, AI's ability to process, analyse, and learn from vast amounts of IoT sensor data empowers organisations to make data-driven decisions, improve operational efficiency, enhance user experiences, and unlock new opportunities for innovation.

The journey towards Industry 4.0

Factory automation, IoT, and generative AI are key components leading towards Industry 4.0, which aims to create smart, interconnected, and highly efficient manufacturing systems. By integrating these IoT sensors with AI, a factory can take significant steps towards achieving Industry 4.0.

image: LevelTec
image: LevelTec

Here's how a factory can start on the journey towards Industry 4.0:

  1. Connectivity and Data Collection: Implement IoT devices and sensors throughout the factory to collect real-time data from machines, equipment, and processes. These devices can capture information such as temperature, pressure, energy consumption, cycle times, and quality metrics. This connectivity allows for seamless data flow and forms the foundation for intelligent decision-making.
  2. Data Analytics and AI: Utilise generative AI algorithms and machine learning techniques to analyse the vast amounts of collected data. AI can identify patterns, correlations, and anomalies to extract valuable insights and optimise operations. These algorithms can be applied to areas such as predictive maintenance, quality control, energy management, and production optimisation.
  3. Predictive Maintenance: By leveraging IoT data and generative AI algorithms, predict potential machine failures or maintenance needs in advance. The system can analyse historical data and machine behaviour patterns to identify signs of impending issues. This proactive maintenance approach minimises unplanned downtime, reduces maintenance costs, and optimises machine performance.
  4. Quality Assurance: IoT sensors can continuously monitor key parameters during the manufacturing process, ensuring quality control. Generative AI algorithms can analyse real-time data to detect anomalies and patterns that indicate product defects. By identifying quality issues early, corrective actions can be taken promptly, minimising waste and enhancing product quality.
  5. Autonomous Operations: Combine IoT and generative AI to enable autonomous operations in certain areas of the factory. For instance, AI-powered robots can handle repetitive or dangerous tasks, such as material handling, assembly, or packaging. These robots can operate independently, using IoT connectivity to communicate and coordinate with other machines and systems.
  6. Optimisation and Efficiency: Generative AI algorithms can analyse production data and optimise various aspects of the manufacturing process. For example, AI can optimise machine settings, production schedules, and material usage to maximise efficiency and reduce costs. By leveraging IoT connectivity, the system can continuously adapt and improve based on real-time feedback and changing conditions.
  7. Human-Machine Collaboration: Industry 4.0 emphasises the collaboration between humans and machines. IoT and generative AI technologies can assist workers by providing real-time data, insights, and guidance. Augmented reality interfaces can overlay relevant information on workers' field of view, enhancing their efficiency and accuracy.

Implementing these technologies requires careful planning, investment, and a phased approach. It's essential to consider factors such as infrastructure requirements, data security, workforce training, and change management. Collaborating with IoT and AI solution providers and consultants with expertise in planning transformation through technology can help ensure a successful transition to a smart factory.

Bega Valley’s circular economy program

Image: Regional Circularity Co-operative Limited
Image: Regional Circularity Co-operative Limited

The most inspiration keynote speaker at the IoT conference was Barry Irvin AM, the executive chairman of Bega, who spoke about harnessing the power of IoT to transform the entire Bega Valley into a circular economy.

Bega Group, which started as Bega Cheese, now owns many brands (including Farmers Union and Vegemite) and has factories across Australia. As a good corporate citizen, Bega has carbon reduction targets, and wishes to operate in a sustainable circular economy.

After piloting projects for a circular economy within Bega Group, Barry was challenged to go large, and he’s now collaborating with local government and businesses to create a circular economy that encompasses the entire Bega Valley.

Image: Regional Circularity Co-operative Limited
Image: Regional Circularity Co-operative Limited

The Bega Valley circular economy aims to solve issues with waste, water, soil, biodiversity, carbon emissions, nutrition, logistics, animal care, community education/innovation/aged care, rural economy/tourism.

At present 91% of resources are used for a single purpose or being wastefully consumed worldwide. The Bega Circular Valley is imagined as a pristine valley that is an innovation hub, with diversified industrial activities, mixed farming that supports biodiversity, dealing with climate change through carbon neutrality and zero waste to landfill.

A cooperative has been established for the initiative, recognising that Bega wouldn’t be able to work in isolation to achieve a circular valley. The ambition of the Bega Valley circular cooperative is to have sensors across the entire valley and have data visualised at a planned Bega Circularity Centre. The vision is for the Bega Valley to become a place that attracts tourists, students, entrepreneurs and investors to experience and participate in this uniquely circular valley.

Want to have a chat?

I hope this blog post has inspired you to consider harnessing the potential of the Internet of Things and Artificial Intelligence to drive innovation and efficiency in your business.

With 35 years of experience in the technology industry, I have the knowledge and skills needed to help you plan the transformation of your business through IoT and AI. If you’d like to talk further about this or anything I’ve written about, get in contact with me today, I’m always happy to meet and have a chat over a coffee.

And don’t forget to check out the list of IoT expo stall holders below, there’s a broad range of services and technology to consider for your IoT/AI driven transformation.

Further reading

ChatGPT, available at https://chat.openai.com/

AI-powered IoT: The rapidly advancing technology that revolutionizes businesses operations, 11 Sep 2018, Vasundhara Bundela, Softwed Solutions, available at https://www.softwebsolutions.com/resources/use-cases-of-AI-powered-IoT.html

Albanese Government launches public consultation to ensure ‘appropriate safeguards’ on AI, 1 June 2021, Clare Armstrong, The Advertiser, available for subscribers at https://www.adelaidenow.com.au/news/national/albanese-government-launches-public-consultation-to-ensure-appropriate-safeguards-on-ai/news-story/ace39c618cc697fefa03b2a542985686

IoT expo stall holders

Sonya Weiser

Sonya Weiser

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