THANK YOU FOR SUBSCRIBING
× 
Applied Technology Review Weekly Brief
Be first to read the latest tech news, Industry Leader's Insights, and CIO interviews of medium and large enterprises exclusively from Applied Technology Review
Digital Strategy on Business outcomes
Applied Technology Review | Tuesday, February 09, 2021
More in News
Material advancements, miniaturization, and digital integration have all contributed to the significant maturity of sensor production. Graphene and piezoelectric materials provide ultra-sensitive sensors to detect changes in the environment. However, in robotics, medical gadgets, and automobile airbags, piezoelectric materials enable effective motion and pressure sensors.
Miniaturization is another key trend in sensor manufacturing. The demand for smaller, more compact devices has driven advancements in microelectromechanical systems (MEMS) technology. MEMS sensors are ubiquitous in everything from smartphones and wearables to automotive systems and industrial equipment. The sensors have tiny mechanical structures and integrated circuits that allow them to measure physical phenomena such as acceleration, temperature, humidity, and pressure. The development of MEMS technology has enabled sensors to be smaller, more reliable, and more energy-efficient, making them ideal for integration into the Internet of Things (IoT) ecosystem.
Wireless sensing technologies have made significant strides. The advent of low-power wireless communication protocols has facilitated the development of wireless sensor networks. The networks enable real-time data collection and monitoring over long distances without wired connections. It has led to the growth of remote monitoring systems in various sectors, such as agriculture, smart cities, and healthcare. Artificial intelligence (AI) and machine learning (ML) are increasingly integrated into sensor technology, enhancing their capabilities. AI and ML algorithms allow sensors to process and analyze large volumes of data in real-time, enabling more accurate predictions and decision-making.
Integrating sensors with cloud computing has unlocked new data storage and analysis possibilities. In healthcare, for example, sensors embedded in wearable devices can track vital signs and send the data to cloud-based platforms for continuous monitoring and analysis by medical professionals. It enhances personalized healthcare and enables remote patient monitoring, which has become especially valuable in global health challenges like the COVID-19 pandemic.
Sustainability is a key driver in sensor technology development. As industries increasingly prioritize environmental responsibility, sensor manufacturers focus on creating eco-friendly products. The advancements in sensor manufacturing are shaping a future where sensors are not only smaller and more powerful but also smarter, more connected, and environmentally friendly. As sensor technologies evolve, they will play a pivotal role in transforming industries and improving the quality of life through enhanced data collection, analysis, and decision-making. ...Read more
A precision-driven, data-centric approach is replacing old, frequently reactive approaches in the global agricultural sector, which is undergoing a significant upheaval. Smart sensors—small but mighty gadgets that collect detailed, real-time data—are at the center of this transformation, empowering farmers to make well-informed decisions that greatly improve production, sustainability, and efficiency. Smart sensors are radically changing the way food is produced, handled, and distributed; this is not just about small tweaks.
Revolutionizing Efficiency Across the Board
The integration of smart sensors into agribusiness offers a range of tangible benefits that are transforming traditional farming practices. Foremost among these is the precision management of resources. By identifying the specific needs of various field zones, farmers can apply water, fertilizers, and pesticides with greater accuracy, resulting in a 20–30 percent reduction in input costs while significantly minimizing environmental impact from runoff and chemical overuse. This targeted approach stands in stark contrast to conventional methods that rely on uniform treatment across entire fields, often leading to inefficiencies and waste.
Another critical advantage is the ability to increase crop yields and quality. Real-time data on soil health, nutrient levels, and plant stress enable timely, proactive interventions that promote healthier plants and enhance productivity. Yield improvements of 10–15 percent are familiar with such technology. In parallel, the continuous data streams generated by smart sensors support improved decision-making. Farmers gain precise, data-driven insights into planting schedules, irrigation needs, fertilization strategies, and pest control measures, optimizing every phase of the agricultural cycle.
Smart sensors facilitate reduced labor costs and greater automation. Remote monitoring, especially when paired with automated systems like smart irrigation, minimizes the need for manual inspections, allowing farm labor to be redirected to other essential tasks. These sensors also support early detection and prevention efforts, identifying signs of disease, pest infestations, or equipment malfunctions before they escalate into significant issues, thereby protecting yields and reducing losses.
The Latest Advancements and Future Outlook
The trajectory of smart sensor technology in agribusiness reflects a pattern of continuous innovation, with transformative advancements reshaping modern farming practices. One key development is the integration of artificial intelligence (AI) and machine learning (ML), which enables the processing of vast datasets generated by sensors. These technologies support predictive analytics that inform critical decisions, ranging from anticipating climate shifts and disease risks to optimizing planting schedules and forecasting yields.
The rollout of 5G connectivity is poised to accelerate this transformation even further. With its ultra-low latency, high reliability, and capacity to connect massive numbers of IoT devices, 5G facilitates uninterrupted data transmission, even from remote agricultural regions. Another notable innovation is the development of biodegradable sensors. Designed to minimize environmental impact, these sensors can be distributed like fertilizer and naturally decompose after use, eliminating the need for retrieval and reducing electronic waste. Many of these systems are also wirelessly powered, eliminating the need for batteries.
In parallel, computer vision technology—particularly when deployed via drones equipped with multispectral and near-infrared cameras—enables high-resolution crop monitoring and early detection of pests across extensive farmland. Complementing these tools, the use of digital twins offers a powerful means for simulation and predictive modeling, thereby enhancing operational planning and efficiency.
Smart sensors are not merely tools; they are the eyes and ears of modern agribusiness, providing unprecedented visibility and control. The future of agriculture is undoubtedly smarter, and sensors are at its very core. ...Read more
Berlin – Grandperspective GmbH, a leading provider of ground-based remote sensing monitoring systems, has set a new high bar for methane detection visibility.
The scanfeld® monitoring system, which uses hyperspectral imaging based on FTIR technology to detect methane and 400 other compounds at rates of 0.005kg/hr or less, has been certified by one of the world’s most respected standards bodies.
In February 2024, a series of controlled-released experiments, which were validated by the Engler-Bunte Institute of the German Technical and Scientific Association for Gas and Water (DVGW) at the Karlsruhe Institute of Technology (KIT), proved that Grandperspective’s remote sensor technology was able to detect methane emissions at leak rates of only 100 grams per hour over a distance of at least 250 metres in real-life conditions. Furthermore, these tests have been fully approved by a global energy corporation, as part of its own efforts to drive down methane emissions.
To ensure that the tests met the necessary standards and specifications set out by the DVGW, Grandperspective deployed three sensors. Two were fixed units from an ongoing pilot study for continuous monitoring, and one was a mobile unit. The three sensor units were deployed to detect a series of simulated methane leaks – at various points within the facility - over a fiveday period.
In total, Grandperspective’s team, who were monitored by a research engineer from the Engler-Bunte Institute, conducted over 80 assessments experimenting with different flow rates and wind speeds, across a range of distances.
The results of these third-party tests were in support of Grandperspective’s unparalleled ability to monitor down to the new EU 17g/h monitoring threshold and at the same time further strengthen the company’s pioneering work in the field of multi-compound and multi-area monitoring. They also shine a light on the vast potential of ground-based continuous monitoring systems. This is because further analysis and evaluation carried out independently of the testing cycle, while working within the same parameters, has revealed that the scanfeld® monitoring system meets the new European Union’s Leak Detection and Repair (LDAR type 1) 17 grams per hour threshold. The next phase of these tests will be to demonstrate the 17g/h threshold similarly independently validated.
Peter Maas, Grandperspective’s Managing Director and Chief Technology Officer, said, “Our goal was to externally and independently validate the methane detection capability of the scanfeld® monitoring system. Achieving the 100 grams per hour threshold from a distance of 250 metres massively exceeds the current limits of conventional monitoring technology which are typically in the order of several kilograms per hour and satellite emission detection limits being as high as 100 kilograms per hour. This is a significant moment for the industry, as by scientifically proving that it is possible to detect and quantify emissions at extremely low detection thresholds using FTIR remote sensing technology for the first time, the sector has a set of tools that can help it to considerably reduce emissions.”
To receive a copy of the report, please contact us at scanfeld@grandperspective.de. ...Read more
Integrating digital twins and generative AI revolutionizes organizations' operations, offering a partnership that enhances efficiency and innovation. These two technologies, each with its distinct value, are proving even more powerful when combined.
What Are Digital Twins and Generative AI?
Digital twins are exact virtual copies of physical assets, processes, or systems that can replicate real-life situations and enhance efficiency. They offer a safe space for experimenting with and enhancing strategies, forecasting results, and improving decision-making. Conversely, generative AI denotes algorithms capable of generating content, like text, images, and simulations, using provided data. This technology is transforming various business processes by automating tasks and generating insights.
The Synergy Between Digital Twins and Generative AI
When utilized alongside digital twins and generative AI, they establish a formidable partnership that can greatly enhance organizational capabilities. Generative AI can streamline the deployment of digital twins by structuring inputs and synthesizing outputs, making the process more efficient. Meanwhile, digital twins provide a robust environment for testing and validating the outputs generated by AI, ensuring accuracy and reliability.
Practical Applications
The practical applications of this pairing are vast. For instance, in manufacturing, digital twins can simulate production processes, while generative AI can optimize these simulations by predicting potential issues and suggesting improvements. This leads to reduced downtime, lower costs, and improved product quality. In healthcare, digital twins of patients can be used to simulate treatment plans, with generative AI providing personalized recommendations based on the latest medical research.
Benefits of Combining These Technologies
The benefits of combining digital twins and generative AI are numerous. Organizations can achieve faster deployment times, reduced costs, and enhanced value from technology investments. This combination also allows for more accurate predictions and better decision-making, ultimately improving operational efficiency and innovation.
Future Outlook
As more organizations recognize the potential of digital twins and generative AI, the adoption of these technologies is expected to grow. The future will likely see even more sophisticated applications and integrations, further enhancing their impact on various industries. Businesses can capitalize on new opportunities and create substantial value by staying ahead of these trends.
In conclusion, pairing digital twins and generative AI represents robust technological advancement. By leveraging both strengths, organizations can achieve greater efficiency, innovation, and value, paving the way for a more advanced and connected future. ...Read more
Copyright © 2026 Applied Technology Review.All Rights Reserved
Top
