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This article’s purpose is to highlight how an IoT platform for structural monitoring can provide innovative solutions for monitoring and managing tunnels. The processes of safety and operations are smooth and sustainable, nonetheless also the software technology provides a safe environment for the users and workers.
Structural monitoring is a process that involves collecting and constantly analyzing data about the health status and safety of a structure, such as a bridge, building, or tunnel. To facilitate this process, sensors and advanced technologies have been introduced in recent years to continuously monitor the structure and identify signs of deterioration or damage. Structural monitoring was created to ensure the safety of structures and prevent accidents or collapses, and it can also help identify problems in advance and plan more efficient and cost-effective maintenance or repair work. It has also proven to be useful in optimising operational processes and ensuring that the structure is used safely and efficiently. In fact, data collected from structural monitoring can be used to assess the reliability of the structure and identify any design or construction problems.
The infrastructures authority are facing increasingly critical challenges in managing tunnels every day, such as safety, maintenance, and durability, but not only:
Industry operators are witnessing a growing need for innovative solutions in tunnel monitoring and management. Specific challenges in tunnel management, such as safety, maintenance, and longevity, require continuous monitoring and efficient management. Innovative solutions, such as IoT structural monitoring platforms, can help overcome these challenges and ensure optimal tunnel management. Let's see how.
Adopting an IoT structural monitoring platform offers numerous advantages, including: safety:
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Data drives discovery. As a consequence one would think that more data would help drive more discovery, or at least accelerate discovery. To access more data oftentimes, one has to aggregate and centralize data from different sources. These sources can be from a variety of devices, instruments, formats, languages, countries and legislations. In the most straightforward approach, data is brought together and (pre-)processed at a single site and analysed centrally at the location of the AI model. This is ‘traditional’ centralized learning.
In practice, data is trapped. Data could be trapped in paper documents, pdfs, or in physical libraries. Intelligent Document Processing is a way to approach this type of unstructured ‘trapped’ data. Alternatively, data can be trapped by ownership, and privacy. As an example, an industrial partner may have an interest in a dataset, and therefore the owner of the data will be less willing to share the data. A patient, or an institution representing the patient, might be restricted to sharing the data for privacy reasons. A technical reason for data being trapped is when a device was developed without the objective of data aggregation, and thus lacking means for data harmonization altogether.
Driven by the advances in the Internet of Things, federated learning (FL) offers a solution, to release data and drive discovery. In FL, the model is trained without seeing or touching the data. Metaphorically speaking, the AI model travels to each dataset rather than data being aggregated at the site of the AI model. FL stimulates data sharing collaborations across sites without compromising patient privacy data legislation, governed by e.g. GDPR and HIPAA. In parallel, FL removes obstacles posed by heterogeneity of local devices or local (clinical) data management systems.
An example in biomedical research: In many instances the number of cases for orphan and rare diseases per institution are too low to garner the benefits of AI assisted prediction capabilities. Here FL trains a machine learning algorithm across multiple decentralized devices or servers, without actually exchanging the data or sharing any sensitive patient data. The federated approach promotes access to maximal data, while lowering institutional burdens to data sharing. Deploying FL over multiple sites and continents, prompted recent breakthroughs in the diagnosis of rare and aggressive cancers, like Triple-negative breast cancer and Glioblastoma. Thereby overcoming the lack of sufficient data for an AI analysis at a single site and thus outperforming the locally trained AI models.
Sensoworks, partner in the Frontiere network of companies, is in the initial phase of developing a FL model in collaboration with the Politecnico di Milano. Different FL architectures and types will be investigated to find the most optimal way to deploy an anomaly detection model on data derived from sensors, for which the benefits of FL outweigh the strenuous efforts of harmonizing data.
Contact: d.r. Remco Foppen
As the digitization process of enterprises advances, the need to protect sensitive information and data is also becoming more pressing. In fact, digital transformation is not just about mere technological advancement: it is also about constant attention to the development of effective strategies to safeguard smart networks from potential cyber-attacks. In this sense, cybersecurity assumes primary importance and must be among the priorities of a company that really wants to call itself innovative and open to the future.
Speaking of 2022 cybersecurity-themed trends, Gartner calculated that by 2025, 45 percent of companies will have been victims of supply chain cyber-attacks. However, companies that adopt mesh architecture will be able to reduce the impact of individual attacks by up to 90%.
In this context, it is more critical than ever for companies to have frameworks that identify hacker attacks, protect technology systems, and detect and neutralize threats. An Industrial Internet of Things (I-IoT) system, in addition to optimizing the production process by making it more efficient, should also include strict security controls. The basic principles of cybersecurity (the so-called "CIA" criteria, Confidentiality, Integrity, Availability) are as valid as ever in an Industry 4.0 context in which, according to Niccolò De Carlo, CEO of Sensoworks, the best approach to create an effective and functional protection system is definitely a holistic one. In fact, attention to data collection, storage, and use must be part of a broader and more comprehensive cybersecurity perspective.
In light of an industrial scenario so fertile with digital opportunities and innovations, Sensoworks stands as a partner able to offer targeted solutions to enable companies to preside over the digital transition and, at the same time, ensure that their data is always adequately protected.
Indeed, security protocols and technologies are fundamental to Sensoworks: in addition to collecting, monitoring, and interpreting data from sensors connected to machinery and infrastructure, the platform is easily configured to best preserve sensitive information.
In addition, the entire production process is protected through blockchain technology, a shared structure that cannot be modified within which data is entered that, once entered, will not be tweaked or deleted— a guarantee of the correct information that is essential to ensure all-around cybersecurity.
We have seen how developing effective strategies to protect data and networks from potential cyber breaches is now imperative. At the same time, however, as Sensoworks CEO De Carlo reminds us, it is also necessary to study effective strategies for the physical security of the infrastructure.
An example of an architecture that involves both physical and technological structure might be an integrated water system. Here, through cyber-infrastructures such as smart water networks, IoT, data-science techniques, augmented intelligence, and, indeed, blockchain, it is possible to make more informed decisions in real-time precisely because of sensors and instrumentation that are in charge of securely collecting and transmitting data.
Thus, one can see how knowledge and data security act to support business decisions, while also giving greater awareness of water consumption and value.
"We are reaching 3.5 billion connected devices globally. Our use of most of these devices to date plays a strategic role for our country," De Carlo points out.
"Let's think for a moment about road infrastructure, power generation infrastructure. They are increasingly connected and need to be preserved from any kind of risk. Thanks to technologies like Sensoworks', it is possible to identify if a device, a sensor, a device is not working properly or if it has been intentionally tampered with."
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Contact Eleonora Stragliotto, Head of Sales, to learn more about how the Sensoworks platform protects sensitive information and data.
