Mattias O'Nils

• Prof. Dr.
• Head of Department at Mid Sweden University

Node lifetime predictions are a crucial design time tool when developing Internet of Things (IoT) solutions with constrained energy budgets. However, this analysis is typically based on simplistic analyses of current consumption values based on datasheets and static duty cycles. This leads to an optimistic prediction of the node lifetime. Real-worl...

The rapid progress in sensor technology and computational capabilities has significantly improved real-time data collection, enabling precise monitoring of various phenomena and industrial processes. However, the volume and complexity of heterogeneous data present substantial processing challenges. Traditional data-processing techniques, such as da...

Reliable methods for bearing fault diagnosis are of great importance because they provide the possibility of preventing failures in machines. A significant challenge is developing solutions that can handle the variances in the data across different domains i.e., the operational context of the bearing and settings including noise, bearing type, rota...

The importance of preventing failures in bearings has led to a large amount of research being conducted to find methods for fault diagnostics and prognostics. Many of these solutions, such as deep learning methods, require a significant amount of data to perform well. This is a reason why publicly available data are important, and there currently e...

Detecting and measuring objects with vision-based systems in uncontrolled environments is a difficult task that today, thanks to the development of increasingly advanced artificial intelligence-based techniques, can be solved with greater ease. In this context, the paper proposes a novel approach for the vision-based measurement of objects in uncon...

Across all industries, digitalization and automation are on the rise under the Industry 4.0 vision, and the forest industry is no exception. The forest industry depends on distributed flows of raw materials to the industry through various phases, wherein the typical workflow of timber loading and offloading is finding traction in using automation a...

Anomaly detection in multivariate time series is valuable for many applications. In this context, unsupervised and semi-supervised deep learning methods that estimate how normal a new observation is have shown promising results on benchmark datasets. These methods are dependent on a threshold that determines which points should be regarded as anoma...

Skin cancers are the most cancers diagnosed worldwide, with an estimated > 1.5 million new cases in 2020. Use of computer-aided diagnosis (CAD) systems for early detection and classification of skin lesions helps reduce skin cancer mortality rates. Inspired by the success of the transformer network in natural language processing (NLP) and the deep...

p>Across all industries, digitalization and automation are on the rise under the Industry 4.0 vision, and the forest industry is no exception. The forest industry depends on distributed flows of raw materials to the industry through various phases, wherein the typical workflow of timber loading and offloading is finding traction in using automation...

p>Across all industries, digitalization and automation are on the rise under the Industry 4.0 vision, and the forest industry is no exception. The forest industry depends on distributed flows of raw materials to the industry through various phases, wherein the typical workflow of timber loading and offloading is finding traction in using automation...

To produce flawless glass containers, continuous monitoring of the glass gob is required. It is essential to ensure production of molten glass gobs with the right shape, temperature, viscosity and weight. At present, manual monitoring is common practice in the glass container industry, which heavily depends on previous experience, operator knowledg...

Skin cancer is one of the most threatening cancers, which spreads to the other parts of the body if not caught and treated early. During the last few years, the integration of deep learning into skin cancer has been a milestone in health care, and dermoscopic images are right at the center of this revolution. This review study focuses on the state-...

The importance of anomaly detection in multivariate time series has led to the development of several prominent deep learning solutions. As a part of the anomaly detection process, the scoring method has shown to be of significant importance when separating non-anomalous points from anomalous ones. At this time, most of the solutions utilize an agg...

Powered wheelchairs have enhanced the mobility and quality of life of people with special needs. The next step in the development of powered wheelchairs is to incorporate sensors and electronic systems for new control applications and capabilities to improve their usability and the safety of their operation, such as obstacle avoidance or autonomous...

Object detection for sky surveillance is a challenging problem due to having small objects in a large volume and a constantly changing background which requires high resolution frames. For example, detecting flying birds in wind farms to prevent their collision with the wind turbines. This paper proposes a YOLOv4-based ensemble model for bird detec...

Image processing systems exploit image information for a purpose determined by the application at hand. The implementation of image processing systems in an Internet of Things (IoT) context is a challenge due to the amount of data in an image processing system, which affects the three main node constraints: memory, latency and energy. One method to...

Optimising the energy consumption of IoT nodes can be tedious due to the due to complex trade-offs involved between processing and communication. In this article, we investigate the partitioning of processing between the sensor node and a server and study the energy trade-offs involved. We propose a method that provides a trade-off analysis for a g...

High temperatures complicate the direct measurements needed for continuous characterization of the properties of molten materials such as glass. However, the assumption that geometrical changes when the molten material is in free-fall can be correlated with material characteristics such as viscosity opens the door to a highly accurate contactless m...

3D object recognition is an generic task in robotics and autonomous vehicles. In this paper, we propose a 3D object recognition approach using a 3D extension of the histogram-of-gradients object descriptor with data captured with a depth camera. The presented method makes use of synthetic objects for training the object classifier, and classify rea...

The rapid development of the Internet of Things is affecting the requirements towards wireless vision sensor networks (WVSN). Future smart camera architectures require battery-operated devices to facilitate deployment for scenarios such as industrial monitoring, environmental monitoring and smart city, consequently imposing constraints on the node...

A multi-camera dome consists of number of cameras arranged in layers to monitor a hemisphere around its center. In volumetric surveillance, a 3D space is required to be monitored which can be achieved by implementing number of multi-camera domes. A monitoring height is considered as a constraint to ensure full coverage of the space below it. Accord...

A three-dimensional (3D) reconstruction method and multi-camera calibration using multiple artificial reference markers have been used for precise volumetric surveillance of fast-flying objects. The method uses a two-layer 3D reconstruction that integrates two multi-camera stereo-nodes. The fields of view of stereo nodes are directed at an acute an...

Deep convolution neural networks (DCNNs) enable effective methods to predict the melanoma classes otherwise found with ultrasonic extraction. However, gathering large datasets in local hospitals in Sweden can take years. Small datasets will result in models with poor accuracy and insufficient generalization ability, which has a great impact on the...

The Internet of Things has grown quickly in the last few years, with a variety of sensing, processing and storage devices interconnected, resulting in high data traffic. While some sensors such as temperature, or humidity sensors produce a few bits of data periodically, imaging sensors output data in the range of megabytes every second. This raises...

In the past three years, deep convolutional neural networks (DCNNs) have achieved promising results in detecting skin cancer. However, improving the accuracy and efficiency of the automatic detection of melanoma is still urgent due to the visual similarity of benign and malignant dermoscopic images. There is also a need for fast and computationally...

Visual monitoring systems employ distributed smart cameras to effectively cover a given area satisfying specific objectives. The choice of camera sensors and lenses and their deployment affects design cost, accuracy of the monitoring system and the ability to position objects within the monitored area. Design cost can be reduced by investigating de...

The Internet of Things introduces Internet connectivity to things and objects in the physical world and thus enables them to communicate with other nodes via the Internet directly. This enables new applications that for example allow seamless process monitoring and control in industrial environments. One core requirement is that the nodes involved...

The Internet of Things (IoT) enables users to gather and analyze data from a large number of devices. Knowledge obtained by these systems is valuable in order to understand, control, and enhance the monitored process. The mass of information to process leads however to new challenges related to required resources for both data processing and data t...

In many industrial fields, the direct measurement of a specific parameter of interest can be too costly to be feasible. Using data from other parameters about the process, a data driven approach can instead be used for a cost-efficient estimation of the parameter of interest. For the Swedish forest industry, the measurement of the timber bundles vo...

Communication is often considered as the most costly component of a wireless sensor node. As a result, a variety of technologies and protocols aim to reduce the energy consumption for the communication especially in the Internet of Things context. In order to select the best suitable technology for a given use case, a tool that allows the compariso...

Due to the limited energy budget for sensor nodes in the Internet of Things (IoT), it is crucial to develop energy efficient communications amongst others. This need leads to the development of various energy-efficient protocols that consider different aspects of the energy status of a node. However, a single protocol covers only one part of the wh...

Networking solutions for the Internet of Things are typically designed for applications that require low data rates and feature rare transmission events. The initial assumption leads to a system design towards minimal data transfers and packet sizes. However, this can become a challenge, if applications require different traffic patterns or coopera...

This paper proposes a method for calibrating of multi-camera systems where no natural reference points exist in the surrounding environment. Monitoring the air space at wind farms is our test case. The goal is to monitor the trajectories of flying birds to prevent them from colliding with rotor blades. Our camera calibration method is based on the...

Volumetric monitoring can be challenging due to having a 3D target space and moving objects within it. Multi camera dome is proposed to provide a hemispherical coverage of the 3D space around it. This paper introduces a method that optimizes multi camera placement for full coverage in volumetric monitoring system. Camera dome placement is modeled i...

The Internet of Things has changed the range of applications for cameras requiring them to be easily deployed for a variety of scenarios indoor and outdoor, while achieving high performance in processing. As a result, future projections emphasise the need for battery operated smart cameras, capable of complex image processing tasks that also commun...

The processing of images at the Vision Sensor Nodes (VSN) requires a high computation power and their transmission requires a large communication bandwidth. The energy budget is limited in outdoor applications of Wireless Vision Sensor Network (WVSN). It means that both the processing of images at the VSN and the communication to server must be ene...

The data reduction capability of image compression schemes is limited by the underlying compression technique. For applications with minor changes between consecutive frames, change coding can be used to further reduce the data. We explored the efficiency of change coding for data reduction in Wireless Visual Sensor Network (WVSN). This paper prese...

Background subtraction is one of the fundamental steps in the image processing pipeline for distinguishing foreground from background. Most of the methods have been investigated with respect to visual images, in which case challenges are different compared to thermal images. Thermal sensors are invariant to light changes and have reduced privacy co...

Multi-camera dome is composed of a number of cameras arranged to monitor a half sphere of the sky. Designing a network of multi-camera domes can be used to monitor flying activities in open large area, such as birds' activities in wind parks. In this paper, we present a method for evaluating the coverage effectiveness of the multi-camera domes plac...

Smart camera systems integrating multi-model image sensors provide better spectral sensitivity and hence better pass-fail decisions. In a given vision system, pre-processing tasks have a ripple effect on output data and pass-fail decision of high level tasks such as feature extraction, classification and recognition. In this work, we investigated f...

The design of multi-camera surveillance system comes with many advantages, for example it facilitates as understanding how flying objects act in a given volume. One possible application is for the observation interaction of birds and calculate their trajectories around wind turbines to create promising systems for preventing bird collisions with tu...

Embedded systems with integrated sensing, processing and wireless communication are driving future connectivity concepts such as Wireless Sensor Networks (WSNs) and Internet of Things (IoTs). Because of resource limitations, there still exists a number of challenges such as low latency and energy consumption to realize these concepts to full potent...

Sky monitoring has many applications but also many challenges to be addressed before it can be realized. Some of the challenges are cost, energy consumption and complex deployment. One way to address these challenges is to compose a camera dome by grouping cameras that monitor a half sphere of the sky. In this paper, we present a model for design e...

Embedded smart cameras are gaining in popularity for a number of real-Time outdoor surveillance applications. However, there are still challenges, i.e., computational latency, variation in illumination, and occlusion. To solve these challenges, multimodal systems, integrating multiple imagers can be utilized. However, trade-off is more stringent re...

Safety-critical applications require robust and real-time surveillance. For such applications, a vision sensor alone can give false positive results because of poor lighting conditions, occlusion, or different weather conditions. In this work, a visual sensor is complemented by an infrared thermal sensor which makes the system more resilient in unf...

Embedded smart camera systems are gaining popularity for a number of real world surveillance applications. However, there are still challenges, i.e. variation in illumination, shadows, occlusion, and weather conditions while employing the vision algorithms in outdoor environments. For safety-critical surveillance applications, the visual sensors ca...

X-ray imaging has been used extensively in the manufacturing industry. In the paper and paperboard industry X-ray imaging has been used for measuring parameters such as coat weight, using mean values of X-ray absorption inline in the manufacturing machines. Recently, an interest has surfaced to image paperboard coating with pixel resolved images sh...

Wireless visual sensor networks provide featurerich information about their surrounding and can thus be used as a universal measurement tool for a great number of applications. Existing solutions, however, have mainly been focused on high sample rate applications, such as video surveillance, object detection and tracking. In this paper, we present...

Many wireless vision sensor networks (WVSNs) applications are characterized to have a low duty cycling. An individual wireless vision sensor node (VSN) in WVSN is required to complete the tasks as quickly as possible. The execution of the tasks can be speeded up by exploiting the inherited parallelism in the tasks by using a hardware platform such...

Wireless Vision Sensor Nodes are considered to have smaller resources and are expected to have a longer lifetime based on the available limited energy. A wireless Vision Sensor Node (VSN) is often characterized to consume more energy in communication as compared to processing. The communication energy can be reduced by reducing the amount of transm...

Wireless Sensor Networks applications with huge amount of data requirements are attracting the utilization of high performance embedded platforms i.e. Field Programmable Gate Arrays (FPGAs) for in-node sensor processing. However, the design complexity, high configuration and static energies of SRAM FPGAs impose challenges for duty cycled applicatio...

A new prototype device has been developed based on a laser triangulation principle to measure online surface topography in the paper and paperboard industries. It characterizes the surface in a wide spatial scale of topography from 0.09–10 mm. The prototype's technique projects a narrow line-of-light perpendicularly onto the moving paper-Web surfac...

Wireless Vision Sensor Networks (WVSNs) is an emerging field which consists of a number of Visual Sensor Nodes (VSNs). Compared to traditional sensor networks, WVSNs operates on two dimensional data, which requires high bandwidth and high energy consumption. In order to minimize the energy consumption, the focus is on finding energy efficient and p...

There are a number of challenges caused by the large amount of data and limited resources such as memory, processing capability, energy consumption, and bandwidth, when implementing vision systems on wireless smart cameras using embedded platforms. It is usual for research in this field to focus on the development of a specific solution for a parti...

Real time surface topography measurement in the paper and paperboard industries is a challenging research field. The existing online techniques measure only a small area of paper surface and estimate topographical irregularities in a narrow scale as a single predictor. Considering the limitations and complications in measuring the surface at high s...

Wireless Visual Sensor Networks (WVSNs) are used for the monitoring of large and inaccessible areas. WVSNs are feasible today due to the advancement in many fields of electronics such as CMOS cameras, low power computing platforms, distributed computing and radio transceivers. The energy budget in a WVSN is limited because of the wireless nature of...

Wireless Visual Sensor Networks (WVSN) are feasible today due to the advancement in many fields of electronics such as Complementary Metal Oxide Semiconductor (CMOS) cameras, low power electronics, distributed computing and radio transceivers. The energy budget in WVSN is limited due to the small form factor of the Visual Sensor Nodes (VSNs) and th...

Wireless vision sensor nodes consist of limited resources such as energy, memory, wireless bandwidth and processing. Thus it becomes necessary to investigate lightweight vision tasks. To highlight the foreground objects, many machine vision applications depend on the background subtraction technique. Traditional background subtraction approaches em...

Wireless vision sensor networks (WVSNs) consist of a number of wireless vision sensor nodes (VSNs) which have limited resources i.e., energy, memory, processing, and wireless bandwidth. The processing and communication energy requirements of individual VSN have been a challenge because of limited energy availability. To meet this challenge, we have...

Visual surveillance systems provide real time monitoring of the events or the environment. The availability of low cost sensors and processors has increased the number of possible applications of these kinds of systems. However, designing an optimized visual surveillance system for a given application is a challenging task, which often becomes a un...

In this paper we have explored different possibilities for partitioning the tasks between hardware, software and locality for the implementation of the vision sensor node, used in wireless vision sensor network. Wireless vision sensor network is an emerging field which combines image sensor, on board computation and communication links. Compared to...

Wireless Visual Sensor Networks (WVSN) is formed by deploying many Visual Sensor Nodes (VSNs) in the field. Typical applications of WVSN include environmental monitoring, health care, industrial process monitoring, stadium/airports monitoring for security reasons and many more. The energy budget in the outdoor applications of WVSN is limited to the...

The current trend in embedded vision systems is to propose bespoke solutions for specific problems as each application has different requirement and constraints. There is no widely used model or benchmark which aims to facilitate generic solutions in embedded vision systems. Providing such model is a challenging task due to the wide number of use c...

A visual sensor network (VSN) is a distributed system of a large number of camera nodes and has useful applications in many areas. The primary difference between a VSN and an ordinary scalar sensor network is the nature and volume of the information. In contrast to scalar sensor networks, a VSN generates two-dimensional data in the form of images....

A visual sensor network (VSN) is a distributed system of a large number of camera nodes, which generates two dimensional data. This paper presents a model of a VSN to track large birds, such as golden eagle, in the sky. The model optimises the placement of camera nodes in VSN. A camera node is modelled as a function of lens focal length and camera...

A Wireless Visual Sensor Network (WVSN) is formed by deploying many Visual Sensor Nodes (VSNs) in the field. After acquiring an image of the area of interest, the VSN performs local processing on it and transmits the result using an embedded wireless transceiver. Wireless data transmission consumes a great deal of energy, where energy consumption i...

The challenges involved in designing a wireless Vision Sensor Node include the reduction in processing and communication energy consumption, in order to maximize its lifetime. This work presents an architecture for a wireless Vision Sensor Node, which consumes low processing and communication energy. The processing energy consumption is reduced by...

Wireless vision sensor networks (WVSNs) have a number of wireless vision sensor nodes (VSNs), often spread over a large geographical area. Each node has an image capturing unit, a battery or alternative energy source, a memory unit, a light source, a wireless link, and a processing unit. The challenges associated with WVSNs include low energy consu...

Wireless Visual Sensor Network (WVSN) is formed by deploying many Visual Sensor Nodes (VSNs) in the field. The VSNs acquire images of the area of interest in the field, perform some local processing on these images and transmit the results using an embedded wireless transceiver. The energy consumption on transmitting the results wirelessly is corre...

In the paper industry, surface topography is the essence of both paper and paperboard, and accurate topographical measurements are equally essential in order to achieve a uniform smooth surface. The traditional laboratory methods measure only a few samples from the entire tambour and there are other obvious limitations to this approach. Online meas...

There are a number of challenges caused by the large amount of data and limited resources when implementing vision systems on wireless smart cameras using embedded platforms. Generally, the common challenges include limited memory, processing capability, the power consumption in the case of battery operated systems, and bandwidth. It is usual for r...

Wireless Visual Sensor Network (WVSN) is an emerging field which combines image sensor, on board computation unit, communication component and energy source. Compared to the traditional wireless sensor network, which operates on one dimensional data, such as temperature, pressure values etc., WVSN operates on two dimensional data (images) which req...

Within both the paper and paperboard industries, real time monitoring and measurement of surface roughness of a paper moving at high velocities is an important and challenging area of research. The uniform surface, for an entire production, can be effectively achieved by monitoring and controlling the paper surface roughness, in real time during th...

Visual Sensor Networks (VSNs) are networks which generate two dimensional data. The major difference between VSN and ordinary sensor network is the large amount of data. In VSN, a large number of camera nodes form a distributed system which can be deployed in many potential applications. In this paper we present a model of the physical parameters o...

A method, generally called oversampling, to reach sub-pixel resolution by taking slightly displaced images of an object is investigated for X-ray applications. By mounting the sensor on a high precision step motor table it is possible to increase the spatial resolution from 55 μm×55 μm to at least 20 μm×20 μm, which is required for quality assuranc...

In this paper, we present an approach that uses information about the FPGA architecture to achieve optimized allocation of embedded memory in real-time video processing system. A cost function defined in terms of required memory sizes, available block- and distributedRAM resources is used to motivate the allocation decision. This work is a high-lev...

X-ray imaging systems such as photon counting pixel detectors have a limited spatial resolution of the pixels, based on the complexity and processing technology of the readout electronics. For X-ray imaging situations where the features of interest are smaller than the imaging system pixel size, and the pixel size cannot be made smaller in the hard...

In this paper we have explored different possibilities for partitioning the tasks between hardware, software and locality for the implementation of the vision sensor node, used in wireless vision sensor network. Wireless vision sensor network is an emerging field which combines image sensor, on board computation and communication links. Compared to...