22 papers · ranked by Valyu relevance
Jingru Zhang, Erjia Cui, Hongzhe Li, Haochang Shou
Wearable devices and digital phenotyping are increasingly used in observational and interventional studies to measure real-time biosignals such as physical activity. However, integrating and comparing data across studies and cohorts remains challenging due to variability in device types, acquisition protocols, and…
Keiji Jindo, Jouke Oenema, Yuta Miyoshi, Fedde Sijbrandij + 4 more
In recent decades, the rapid advancement of sensor technologies has revolutionized research in grassland ecosystems. A wide array of sensor technologies has significantly enhanced field-based studies, contributing to a deeper understanding of grassland conditions. This review examines the synergistic potential of…
Gift Nwatuzie, Hassan Peyravi, Rosario Schiano Lo Moriello
Automated monitoring systems increasingly leverage diverse sensing sources, yet a disconnect often persists between machine vision and IoT sensor pipelines. While IoT sensors provide reliable point measurements and cameras offer rich spatial context, their independent operation limits coherent environmental…
Bonface O. Manono, Boniface Mwami, Sylvester Mutavi, Faith Nzilu + 1 more
The agricultural sector, a vital industry for human survival and a primary source of food and raw materials, faces increasing pressure due to global population growth and environmental strains. Productivity, efficiency, and sustainability constraints are preventing traditional farming methods from adequately meeting…
Ali Jia, Ziwei Cai, Xiaoyuan Liu, Kechen Zheng + 2 more
With the rapid development of artificial intelligence technology, the transportation, industry, and healthcare fields are undergoing an intelligent evolution. These advancements have raised higher requirements for technologies such as mobile robots, wearable intelligent agents, self-driving cars, and unmanned aerial…
Ashutosh Tiwari, Gitanjali Mishra, Jagdish Narayan, Ewa Korzeniewska
Conventional sensing systems rely on sequential architectures in which signal acquisition, processing, and decision-making are physically and functionally separated. This paradigm imposes limitations in latency, energy efficiency, and adaptability, particularly in data-intensive and dynamic environments. In this…
Lu Zhang, Yi Du, Haolong Li, Shiquan Yan + 5 more
Driven by the profound convergence of the Internet of Things (IoT) and ubiquitous computing, wearable multifunctional sensors have emerged as a key technology for high-precision human activity recognition (HAR). Advancements in novel materials and flexible electronics have propelled the evolution of these sensors…
Dehury, Chinmaya Kumar, Lovén, Lauri + 6 more
—Industry demands are growing for hyper-distributed applications that span from the cloud to the edge in domains such as smart manufacturing, transportation, and agriculture. Yet today's solutions struggle to meet these demands due to inherent limitations in scalability, interoperability, and trust. In this article, we…
Botong Ou, Baijian Yang
As the expansion of IoT connectivity continues to provide qualityof-life improvements around the world, they simultaneously introduce increasing privacy and security concerns. The lack of a clear definition in managing shared and protected access to IoT sensors offer channels by which devices can be compromised and…
Sanggeon Yun, Ryozo Masukawa, Minhyoung Na, Hyunwoo Oh + 4 more
Autonomous systems and smart-industry deployments increasingly split computation across near-sensor, edge, and cloud resources, where tight energy, latency, and reliability budgets demand run-time adaptivity. In practice, deciding what to compute and transmit at each point is pivotal; yet as multimodal sensor suites…
Duarte, Mariana M. Garcez, Nugroho, Dwi P. A. + 16 more
The increasing use of Internet-of-Things (IoT) sensors in moving objects has resulted in vast amounts of spatiotemporal streaming data. To analyze this data in situ, real-time spatiotemporal processing is needed. However, current stream processing systems designed for IoT environments often lack spatiotemporal…
Authors not listed
Non-invasive biomarker assessment in saliva offers a promising route for early detection of bovine respiratory disease (BRD) and scour in calves. However, accurate electrochemical sensing in this complex matrix remains challenging due to variable pH, viscosity, and interfering species. Here, we report an integrated…
Kai-Chun Lin, Marc Dandin
We report a 0.18 µm CMOS lab-on-a-chip system that monolithically integrates a passive radio frequency identification (RFID) interface and an 8 × 8 array of capacitance sensors configured for measuring the capacitance change resulting from an overlying biological specimen. This lab-on-CMOS platform is designed to…
Mohammad Zoofaghari, Aliakbar Rahimifard, Saikat Chatterjee, Ilangko Balasingham
Goal-oriented semantic communication has recently emerged in wireless sensor-actuator networks, emphasizing the meaning and relevance of information over raw data delivery, thereby enabling resource-efficient telecommunication. This paradigm offers significant benefits for intra-body or implantable sensor-actuator…
Lingsheng Meng, Parker McDonnell, Kaushik Jayaram, Jean-Michel Mongeau
Soft robotic sensors today struggle to interpret complex tactile scenes without incurring significant computational costs. Inspired by insect antennae—compliant, distributed sensors that efficiently process tactile information through physical intelligence—we investigated whether mechanical design and active touch…
Martin Malthe Borch, Pauline Kehr, Rafael Altamirano Torres, Philip J. Gorter de Vries + 3 more
Gas production and consumption is a direct consequence of microbial activity in environmental and industrial settings. In closed batch cultivations, headspace pressure changes therefore give valuable insights into the microbial metabolism. For laboratory scale anaerobic batch cultivations, manual manometer measurements…
Samuel Crouse, Williams Johnston, Qian-Quan Sun
The development of a new integrated operant system was driven by two challenges in behavioral neuroscience: the high cost and technical complexity of commercial rigs, and their limited adaptability across experiments. We developed the NeuroHab, an integrated behavioral arena for high-fidelity operant conditioning and…
Authors not listed
Despite the promise of self-driving laboratories to accelerate discovery, their widespread implementation is hindered by prohibitive cost and technical complexity. We introduce BrickSDLab, a fully functional self-driving lab platform built entirely from LEGO® components, designed to bridge this accessibility gap.…
Kenji Saito
Sensor data in IoT (Internet of Things) systems is vulnerable to tampering or falsification when transmitted through untrusted services. This is critical because such data increasingly underpins realworld decisions in domains such as logistics, healthcare, and other critical infrastructure. We propose a general method…
Authors not listed
Machine olfaction—the artificial replication of the sense of smell—faces significant challenges due to the absence of large, standardized training datasets. Unlike vision, language, and audio models, which benefit from extensive corpora such as ImageNet, GLUE, and AudioSet, olfaction lacks scaled equivalents and…
Authors not listed
Global food security and environmental sustainability are closely linked to positive plant-soil feedback, for example through reduced dependence on synthetic agrochemicals. Beyond their nutritional value as protein- and lipid-rich crops, legumes have an essential ecological function by enhancing soil fertility and…
Authors not listed
The process of label selection holds significant importance in the field of electrochemical biosensors, as it directly impacts the achievement of low detection limits and a wide dynamic range. To attain these objectives, it is necessary to take into account several aspects, including low electroactive potential, high…