Applied Technology Review : News

In healthcare, digital twins are computer representations of systems ranging from patients to hospitals and everything in between, including both physical items and processes. The digital counterparts include electronic health records (EHRs), disease registries, and omics data, such as proteomic, genomic, metabolomic, and bionic data, as well as demographic and lifestyle information for each individual. The introduction of new technologies powered by IoT and AI, combined with the widespread availability of multidimensional data such as behavioral, biometric, cognitive, emotional, and psychological information, has significantly increased the exploration and utility of digital twins. When fully utilized, digital twins for healthcare may provide a breakthrough paradigm for the future management of lifestyle, health, wellness, and chronic diseases. For example, these virtual models may be constantly updated with data from wearable devices, mobile health apps, and other types of self-reported data. This would provide healthcare providers with previously unknown information, which would be useful in developing correct treatment guidelines and tailored advice. Significant advantages of digital twin technology in healthcare are listed below:  Improved patient care: A doctor might simulate therapies for a patient using their digital twin, assisting in making key decisions before treating the patient. Such an approach aims to improve process safety while also enhancing the standard of care. Education and augmented training: Digital twins will be an essential platform for improving the training and education of medical and nursing students and healthcare workers. They provide learners with an interactive platform to better understand complex surgical procedures and human body issues. Predictive maintenance: Digital twins could be utilized to predict failure scenarios and perform predictive maintenance on essential medical devices in the healthcare setting. This will allow healthcare providers to continuously monitor gadget performance in order to predict any malfunctions that might occur during critical medical work operations. Research and development: Digital twining is a significant tool in the course of medical studies. These virtual copies serve as platforms for conducting various scientific studies and delving into the complexities of genetic abnormalities. This can significantly improve healthcare approaches and medical treatment procedures, particularly for rare and severe patients. Enhancement of medical systems: Digital twins enable healthcare organizations to identify operational inefficiencies and bottlenecks in their systems. Managers can maximize resources by conducting proactive analysis and improving patient flow and service delivery. ...Read more

Integrating IoT, blockchain technology, and deep learning models has revolutionized smart home automation, providing enhanced security, efficiency, and autonomy. This integration optimizes energy usage, improves security, and streamlines daily routines, paving the way for a new era in household management.  Security vulnerabilities have become a significant concern with the proliferation of IoT devices. By leveraging blockchain's decentralized and immutable ledger, smart home systems can ensure the integrity and security of data exchanges between devices. Each transaction or data transfer is recorded tamper-proof across multiple nodes, eradicating the risk of a single point of failure or unauthorized access. Blockchain facilitates secure peer-to-peer transactions and automated smart contracts. Devices can autonomously interact and transact based on predefined conditions without intermediaries. Combining IoT connectivity, blockchain security, and deep learning intelligence can enhance homeowners' convenience, efficiency, and peace of mind.  A smart thermostat could adjust the temperature based on real-time weather data retrieved from decentralized sources, all executed through smart contracts recorded on the blockchain. Deep learning models further enhance the capabilities of IoT-based smart home automation by enabling predictive analytics and personalized experiences. These models can analyze historical data from IoT devices to identify patterns, preferences, and anomalies. A deep learning algorithm could learn the occupants' daily routines and adjust lighting, temperature, and other settings to optimize comfort and energy efficiency. Deep learning-powered anomaly detection algorithms can identify unusual behavior patterns indicative of security breaches or malfunctions. For instance, if a security camera detects unusual movements while the occupants are away, the system can trigger alerts and take appropriate actions, such as notifying the homeowners or activating additional security measures. The critical challenge in implementing IoT-based smart home automation with blockchain and deep learning is interoperability and standardization. With various devices from different manufacturers operating on multiple protocols, ensuring seamless integration and compatibility can be complex.  Initiatives such as developing open-source protocols and industry standards aim to address these challenges and foster a more cohesive ecosystem. Privacy and data ownership are critical considerations when deploying smart home systems. With sensitive data being generated and exchanged among devices, ensuring user consent, data encryption, and transparent data handling practices are paramount. Blockchain-based identity management solutions can give users control over their data, allowing them to specify who can access it and under what conditions. Integrating IoT, blockchain, and deep learning models holds immense potential for revolutionizing smart home automation. ...Read more

Traditional soil development techniques are threatened by the growing urbanization and industrialization of the world. Traditionally, cement and chemical grouts (such as sodium silicate, acrylate, and epoxy) are utilized to increase soil strength. However, these methods can cause severe disturbances, pollute the environment, and are difficult to apply broadly. Nanomaterials for Soil Improvement Materials that are smaller than 100 nm and have a wide range of mechanical, optical, electrical, and biological capabilities are referred to as nanomaterials. Laponite, bentonite, colloidal silica, and carbon nanotubes (CNTs) are the four major nanomaterials to improve soil. Additional nanomaterials used to enhance soil characteristics include fullerenes, titanium dioxide (TiO2), zinc oxide (ZnO), bimetallic nanoparticles, nanoscale zerovalent iron (nZVI), and multiwalled carbon nanotubes (MWCNTs).  The Fundamental Process of Nanomaterials for Increasing Soil Density The soil is a three-phase media comprising soil particles, water, and air. The pore water pressure significantly influences the amount of soil strength. Nanomaterials strengthen soil by altering the pore fluid and enhancing the connection between the particles. Due to their small size, nanoparticles are generally well-suited to disperse into finer soil particles not subjected to strong pressure in the pore spaces between them. The microstructure of nanoparticles affects the strength of the soil when they are applied. Compared to three-dimensional nanoparticles (like colloidal silica), the two-dimensional structure of nanoparticles (like CNT) has a different effect on the soil. Because certain soil nanoparticles interact in a nanoparticle-water suspension, their capacity to strengthen soil is influenced by the rheological features of the suspension. The specific surface area of the nanoparticle increases as the particle size decreases. This suggests a higher atomic surface area, which results in a greater capacity for ion exchange and a higher level of particle contact. The presence of nanoparticles enhances the buildup of pore water. Thus, the plastic and liquid limits are larger in soil that contains nanoparticles. This demonstrates that quantum mechanical theories are more applicable than classical mechanics, explaining particles' motion state and energy at the nanoscale level. Benefits of Using Nanomaterials for Soil Improvement Techniques Instead of Conventional Materials As was already established, adding nanomaterials like colloidal silica and carbon nanotubes (CNTs) greatly increases the strength of the soil, especially its compressive strength and resistance to liquefaction. Utilizing nanoparticles is more economical and environmentally favorable than conventional grout materials. Conventional methods of improving soil, including mechanical reinforcements, come with a hefty price tag and negative environmental effects. Another popular method for enhancing soil strength is chemical grouting, which entails putting designed slurries in the desired location. A pressure transmission mechanism then compresses it to reinforce the flimsy base. Cement and solutions, like epoxy, sodium silicate, and acrylate, are frequently used as grouting materials. Since high-pressure infusion is unnecessary when adding nanomaterials as stabilizers, environmental disturbance can be greatly reduced. This method works in both developed areas with buildings and barren terrain. The soil and groundwater aquifers are not harmed by the nanomaterials used to improve soil since they are non-toxic and inert. Furthermore, this method is economical because relatively few nanomaterials are needed for efficient soil fortification. ...Read more