Forum Junge Spitzenforschung
Topic 2023: Sensors & Data Analytics in practical application
A great number of processes and products that we know today would not be possible without sensors and systems that measure and analyse data. Sensors and data analysis are becoming increasingly important. Research on sensors, as well as systems for the analysis of sensor-based data, thus lays the foundation for many future technologies.
Within the framework of the Forum for Young Leading Research, the Foundation for Industrial Research and Humboldt-Innovation GmbH, in collaboration with Berlin's universities including the Freie Universität Berlin, Humboldt-Universität zu Berlin, and Technische Universität Berlin, as well as Charité – Universitätsmedizin Berlin, are seeking innovative application ideas from emerging researchers of any discipline. These ideas should be based on their excellent research with sensors and the analysis of sensor-captured data and should expand the horizon of sensor-based future technologies.
Innovative sensors and data analysis are more efficient, resilient, smarter, and often possess entirely new features, which in turn enable exciting future technologies. They contribute to preserving or enabling a more livable future by addressing cross-cutting issues such as sustainability requirements or innovations in the field of health and quality of life. From nutrient analysis & quality management in the food industry to autonomous driving, warning systems, and virtual reality applications—below is a non-exhaustive list of examples of the application of sensors and sensor-supported data analysis systems:
Efficient and precise sensors are crucial wherever fineness and accuracy are required, such as with medical assistant robots and/or measurements under challenging operational and environmental conditions (noise, electromagnetic radiation, heat, etc.). Supported by artificial intelligence and machine learning, sensor-based data is an integral part of many innovations in process optimization and efficiency improvement. For example, in agriculture, where the measurement and analysis of pH levels or moisture enable the optimization of fertilizer application, irrigation, and yield. Or in cities, where traffic flows can be captured by optical sensors and adjusted in real-time through intelligent data analysis..
Data analysis and sensors are key components of predictive maintenance and real-time monitoring systems. For example, in production for monitoring wear and tear on machinery or in building maintenance. In this way, repair and maintenance measures can be taken in a timely manner, increasing durability and lifespan and preventing costly failures. The durability of the sensors themselves can also enable and improve many technologies, for example, when blood sugar levels are continuously measured by a subcutaneous sensor—increased durability of the sensor means fewer invasive procedures for the patient.
Smart sensor-driven systems include Internet of Things applications or holistic concepts such as Smart City or Industry 4.0. These applications collect and analyse environmental data to enable automations or to act based on conditions and events. Home security systems, automated heating and lighting control, urban traffic and emission monitoring, and level-dependent emptying of waste containers in intelligent waste management are just a few examples of such applications. Even small electronic devices like smartphones and smartwatches are reliant on sensors and data analysis; from facial recognition to pulse measurement and pedometers.
New properties of sensors allow for new innovations and application areas. For example, 3D-printable sensors enable the integration of sensor technology into individually tailored products or prototypes. Work and production processes enhanced with sensor-supported augmented reality applications can provide additional information and make work easier for humans. Smart Clothes, thanks in part to integrated sensors, are not just fashionable or functional but also possess new capabilities such as capturing and monitoring biometric data.
Fairness & Social Justice
How can technological innovations in the field of sensors and data analysis contribute to reducing social injustice and maintaining societal values? For example, by focusing on the most vulnerable in our society. Heat maps that analyse and display climate and temperature data can inform where in the city it is hottest during hot summers, advising vulnerable groups like the elderly where they can cool down. Holistically conceived sensor and data analysis systems, which include data transparency and protection in the design at the hardware or software level, contribute to users' data sovereignty.
Zero Waste and Circular Economy are two concepts that aim to lead to a socially sustainable lifestyle and economy. Innovations in sensor technology and data analysis can make a contribution to tackling this significant societal challenge: In the food industry, they can help reduce food waste by monitoring the freshness of products. In production, they minimize rejects. The collection, identification, and evaluation of used spare parts introduce circular economy features into industrial maintenance. Even the sensors themselves could be sustainably designed: For instance, Swiss researchers have recently succeeded in creating biodegradable and 3D-printable sensors based on cellulose.
Conservation of Resources
Many resources are already scarce today, not least due to climate change. Sensors and data analysis systems can contribute to distributing resources efficiently and thus conserving them. Through the measurement of soil moisture, precipitation, sap flow, etc., the optimal watering amount can be determined, thereby saving water. Comprehensive smart sensor systems in buildings can reduce energy and heat consumption by optimizing room temperature or lighting through sensor-provided data.
Climate Friendliness & Neutrality
Many technologies and our lifestyle as a society have a negative and lasting impact on the environment and climate. Sensors and intelligent data analysis can be a component on the path towards a climate-friendly and neutral future. Among other things, emissions can be monitored or climate data can be collected and processed to possibly initiate countermeasures or increase the yield of renewable energy sources, such as through solar trackers for the optimal alignment of photovoltaic systems. A climate-neutral production and construction method for sensors is desirable among the innovations.
Health & Quality of Life
In the field of medicine and e-health, as well as wearables, many innovations are sensor- and data-driven. They can be used in healthcare to monitor patients' vital signs, thereby improving and potentially adapting treatment in real-time. Additionally, they can assist older individuals in their daily lives, for example through fall detection or medication reminders. In sports science, sensors and the analysis of biometric and movement data help optimize training and prevent injuries. In the area of food quality, the nutrient content of foods can be determined. Thanks to sensors, air pollution levels can also be detected and processed to possibly counteract with appropriate measures.
Inclusion & Gender Equality
As part of innovations for societal participation and inclusion, sensors and data are playing an increasingly important role. For example, in prosthetics where they enable wireless muscle signal transmission or sensory feedback, in ambient assisted living systems that enable older, impaired people to live independently, or as 3D scanners that assist blind people in navigation. Without suitable data processing and analysis, a technical translation of sign language into text or speech and back would not be possible. Also, most current models, disease pictures, etc., are based predominantly on male data. Often termed as Femtech, innovations are therefore shifting the focus onto non-male individuals and their specific needs.
Robust sensor-supported distribution systems can contribute to supply security through data analysis by predicting shortages or failures and redirecting resources. For example, in the energy sector, to continue supplying critical infrastructures like hospitals with power during outages or to detect defects in heat or water distribution systems early enough to take preventive measures. They can be used in logistics to monitor the supply chain to avoid failures or delays, or to monitor transport and storage conditions (humidity, temperature, etc.) to protect fragile goods like food.