Related papers: Time/Computationally Optimal Network Architecture:…
In this work, we present a method that exploits a scenario with inter-Wireless Sensor Networks (WSNs) information exchange by making predictions and adapting the workload of a WSN according to their outcomes. We show the feasibility of an…
Sensor fusion has wide applications in many domains including health care and autonomous systems. While the advent of deep learning has enabled promising multi-modal fusion of high-level features and end-to-end sensor fusion solutions,…
Non-Gaussian and multimodal distributions are an important part of many recent robust sensor fusion algorithms. In difference to robust cost functions, they are probabilistically founded and have good convergence properties. Since their…
The systems based on intelligent sensors are currently expanding, due to theirs functions and theirs performances of intelligence: transmitting and receiving data in real-time, computation and processing algorithms, metrology remote,…
In this paper we have analyzed energy efficient neighbour selection algorithms for routing in wireless sensor networks. Since energy saving or consumption is an important aspect of wireless sensor networks, its precise usage is highly…
In this report, we introduce the concept of co-community structure in time-varying networks. We propose a novel optimization algorithm to rapidly detect co-community structure in these networks. Both theoretical and numerical results show…
In the context of deep learning, this article presents an original deep network, namely CentralNet, for the fusion of information coming from different sensors. This approach is designed to efficiently and automatically balance the…
Wireless systems are expanding their purposes, from merely connecting humans and things to connecting intelligence and opportunistically sensing of the environment through radio-frequency signals. In this paper, we introduce the concept of…
Time synchronization is a critical task in robotic computing such as autonomous driving. In the past few years, as we developed advanced robotic applications, our synchronization system has evolved as well. In this paper, we first introduce…
Wireless sensor networks increasingly become viable solutions to many challenging problems and will successively be deployed in many areas in the future. However, deploying new technology without security in mind has often proved to be…
Cryptography techniques are essential for a robust and stable security design of a system to mitigate the risk of external attacks and thus improve its efficiency. Wireless Sensor Networks (WSNs) play a pivotal role in sensing, monitoring,…
Time synchronization is important for a variety of applications in wireless sensor networks including scheduling communication resources, coordinating sensor wake/sleep cycles, and aligning signals for distributed transmission/reception.…
A wireless sensor network (WSN) has important applications such as remote environmental monitoring and target tracking. In addition, Wireless Sensor networks is an emerging technology and have great potential to be employed in critical…
Sensor fusion is critical to perception systems for task domains such as autonomous driving and robotics. Recently, the Transformer integrated with CNN has demonstrated high performance in sensor fusion for various perception tasks. In this…
Sensor fusion is a technique used to combine sensors with different noise characteristics into a super sensor that has superior noise performance. To achieve sensor fusion, complementary filters are used in current gravitational-wave…
We consider a single-hop data gathering sensor cluster consisting of a set of sensors that need to transmit data periodically to a base-station. We are interested in maximizing the lifetime of this network. Even though the setting of our…
This paper investigates the integration of data sensor fusion in digital twin technology to bolster home environment capabilities, particularly in the context of challenges brought on by the coronavirus pandemic and its economic effects.…
We present ConFusion, an open-source package for online sensor fusion for robotic applications. ConFusion is a modular framework for fusing measurements from many heterogeneous sensors within a moving horizon estimator. ConFusion offers…
Neuromorphic architectures are ideally suited for the implementation of smart sensors able to react, learn, and respond to a changing environment. Our work uses the insect brain as a model to understand how heterogeneous architectures,…
Wireless communication systems exhibit structural and functional similarities to neural networks: signals propagate through cascaded elements, interact with the environment, and undergo transformations. Building upon this perspective, we…