In Norway, Sweden and Finland approximately 9.000 reindeer are killed every year in traffic accidents (road and railway). In field experiments two different electronically sensor system were used. The purpose is to warn car drivers and railway engineers that reindeer are close to, or on the traffic system, and reduce the numbers of accident. The information system developed by Telespor is based on GPS/GSM radio collars. These collars use SMS to inform that the reindeer are close to the traffic system. In addition to the warning, the reindeer owners get information about the reindeer land use throughout the whole year. The collars are expensive (approx. 250 euros/unit) and need battery change every year. At Umeå University a system based on wireless sensor nodes attached to the reindeer collars is developed. This node will send out a periodic warning radio beacon. On road sticks a warning device will be attached containing a radio receiver and LED flashlights that will warn if a radio beacon is received. To further increase the warning distance it is possible to use communication between the roadside warning devices and let several devices flash their LED lights when a reindeer is detected. The radio collar (approx. 15 euros/unit) will have a theoretical battery life of more than 10 years. The radio range is around 500 meters between the radio collar and the roadside warning device, which is more than sufficient.
This paper proposes an intuitive wireless sensor/actuator based communication network for human animal interaction for a digital zoo. In order to enhance effective observation and control over wild life, we have built a wireless sensor network. 25 video transmitting nodes are installed for animal behavior observation and experimental vibrotactile collars have been designed for effective control in an animal park.
The goal of our research is two-folded. Firstly, to provide an interaction between digital users and animals, and monitor the animal behavior for safety purposes. Secondly, we investigate how animals can be controlled or trained based on vibrotactile stimuli instead of electric stimuli.
We have designed a multimedia sensor network for human animal machine interaction. We have evaluated the effect of human animal machine state communication model in field experiments.
In this paper a conceptual model for a social media game will be illustrated. The idea is to find a way to integrate our physical and digital world in a way that will involve the environment around us containing both artifacts and people and become a natural part of our daily lives. We want to show that by integrate ubiquitous information and social media in a game idea, it is possible to create a concept for a social media game application that could be used at a tourist attraction, e.g. a zoo. The value that is received from this application is both educative for the visitors and marketing for the tourist attraction. The conceptual model of the social media game builds upon the foundations of internet of things for the future version of a tourist attraction, such as the Digital Zoo.
In this paper we will describe a positioning system based on synchronized IR light. Each node will be assigned a timeslot where they will send out an IR light. There is an IR camera that is also synchronized to the timeslots that will detect the position of each node and the ID that corresponds to the timeslot. To synchronize the clock of all nodes an IR flashlight is sent out that is detected by a photodiode on the nodes. The demo will show live video stream from a network camera where the ID and position of each node in view will be overlaid in real-time in the video.
Collisions between vehicles and animals have increased in Norway and Europe over the last 40 years, causing economical losses as well as poor welfare for animals and people. In Norway 2 m high deer fences have been put up to prevent killings of semi-domestic reindeer at some limited road- and railway distances. However, these are very expensive and animal passages are needed. As a supplementary measure, an electronic system, aimed at warning the driver if reindeer are close to the road, was tested along the E6 main road at Saltfjellet, Norway, during March - April 2018. 235 female reindeer were equipped with radio transmitter collars (805.15.4 866 MHz). The animals were grazing in a collision exposed area at Saltfjellet. A total of 41 receivers were mounted on road sticks alongside the 4.5 km test distance. When a reindeer with transmitter was within 50 - 100 m proximity to a road stick, the receiver started blinking red. Saltfjellet reindeer herding district lost 15 reindeer in the test area from December 2017 until test start in February 2018. No reindeer were hit by cars during the test period. Nevertheless, 25% of the receivers became defective after a while, most possibly due to battery shortage. A new generation of transmitters and receivers was tested at Saltfjellet during December 2018 - April 2019. Preliminary results from this extended test are presented. We evaluate the electronic warning system as promising. However, improvements are needed in order to achieve optimal receiver and transmitter reliability in function.
In this paper the authors present an approach to provide efficient low-complexity encoding for the block-based video coding scheme. The authors present a method based on removing the most time-consuming task, that is motion estimation, from the encoder. Instead the decoder will perform motion prediction based on the available decoded frame and send the predicted motion vectors to the encoder. The results presented are based on a modified H.264 implementation. The results show that this approach can provide rather good coding efficiency even for relatively high network delays.
Most computing and communicating devices have been personal computers that were connected to Internet through a fixed network connection. It is believed that future communication devices will not be of this type. Instead the intelligence and communication capability will move into various objects that surround us. This is often referred to as the "Internet of Things" or "Wireless Embedded Internet". This thesis deals with video processing and communication in these types of systems.
One application scenario that is dealt with in this thesis is real-time video transmission over wireless ad-hoc networks. Here a set of devices automatically form a network and start to communicate without the need for any previous infrastructure. These devices act as both hosts and routers and can build up large networks where they forward information for each other. We have identified two major problems when sending real-time video over wireless ad-hoc networks. One is the reactive design used by most ad-hoc routing protocols. When nodes move some links that are used in the communication path between the sender and the receiver may disappear. The reactive routing protocols wait until some links on the path breaks and then start to search for a new path. This will lead to long interruptions in packet delivery and does not work well for real-time video transmission. Instead we propose an approach where we identify when a route is about to break and start to search for new routes before this happen. This is called a proactive approach. Another problem is that video codecs are very sensitive for packet losses and at the same time the wireless ad-hoc network is very error prone. The most common way to handle lost packets in video codecs is to periodically insert frames that are not predictively coded. This method periodically corrects errors regardless there has been an error or not. The method we propose is to insert frames that are not predictively coded directly after a packet has been lost, and only if a packet has been lost.
Another area that is dealt with in this thesis is video sensor networks. These are small devices that have communication and computational capacity, they are equipped with an image sensor so that they can capture video. Since these devices in general have very limited resources in terms of energy, computation, communication and memory they demand a lot of the video compression algorithms used. In standard video compression algorithms the complexity is high for the encoder while the decoder has low complexity and is just passively controlled by the encoder. We propose video compression algorithms for wireless video sensor networks where complexity is reduced in the encoder by moving some of the image analysis to the decoder side. We have implemented our approach on actual low-power sensor nodes to test our developed algorithms.
Finally we have built a "Digital Zoo" that is a complete system including a large scale outdoor video sensor network. The goal is to use the collected data from the video sensor network to create new experiences for physical visitors in the zoo, or "cyber" visitors from home. Here several topics that relate to practical deployments of sensor networks are addressed.
In this paper we suggest a promising solution to come over the problems of delivering e-learning to areas with lack or deficiencies in infrastructure for Internet and mobile communication. We present a simple, reasonably priced and efficient communication platform for providing e-learning. This platform is based on wireless ad-hoc networks. We also present a preemptive routing protocol suitable for real-time video communication over wireless ad-hoc networks. Our results show that this routing protocol can significantly improve the quality of the received video. This makes our suggested system not only good to overcome the infrastructure barrier but even capable of delivering a high quality e-learning material.
In this paper we investigate important issue for real-time video over wireless ad-hoc networks on different layers. Many error control methods for this approach use multiple streams and multipath routing. Thus the new proactive, link-state routing protocol have been developed, where the protocol finds the available route in the network and also it will not cause any interruption in the video traffic between the source and the destination. The open source MPEG-4 is also implemented to get the efficient video quality for the picture.
Connectivity in ad-hoc networks is a fundamental, but to a large extend still unsolved problem. In this paper we consider the connectivity problem when a number of nodes are uniformly distributed within a unit square. We limit our problem to the one-hop and two-hop connectivity. For the one-hop connectivity we find the exact analytically solution. For the two-hop connectivity we find the lower and upper bound for connectivity.
Mobile TV is a new interesting area in the telecommunication industry. The technology for sending live video to mobile clients is characterized by relatively low CPU processing power, low network resources, and low display resolution. In this paper we discuss a solution to all of these problems by using application layer multicasting. This can significantly reduce the needed bitrate and required computing resources for each client. At the same time the received video quality is increased. Several different methods for splitting the video into substreams are discussed. Simulations for the local wireless ad-hoc network are performed. A system for application layer multicasting using layered H.264 is also presented.
Sending video over wireless sensor networks is a challenging task. The encoding and transmission of video is very resource hungry and the sensor nodes have very limited resources in terms of communication bandwidth,memory, computation and typically 5-10 times. In this paper we will present a practical implementation of a Wyner-Ziv video codec where the reversed asymmetry in complexity between encoder and decoder can be achieved. We will also present our sensor network platform used in this demonstration known as Fleck TM-3 as well as two different co-processor daughterboards for image processing. The different daughterboards are then compared in terms of speed and energy consumption.
Wyner-Ziv video coding can provide low complexity encoding and high complexity decoding and is therefore a promising approach for video coding in wireless sensor networks. We will demonstrate our practical implementation of a wyner-ziv video codec. The hardware platform used in our camera sensor network is the Fleck camera developed by CSIRO ASL in Brisbane, Australia.
In this paper we present an approach to provide efficient low-complexity video encoding for wireless sensor networks. We present an method based on removing the most time-consuming task, that is motion estimation, from the encoder. Instead the decoder will perform motion prediction based on the available decoded frame and send the predicted motion vectors to the encoder. We present results based on a modified H.264 implementation. Our results shows that this approach can provide rather good coding efficiency even for relatively high network delays.
In this paper we present our approach to use a combination of radio frequency identification (RFID) and a wireless camera sensor network to identify and track animals at a zoo. We have developed and installed 25 cameras covering the whole zoo. The cameras are totally autonomous and they are configuring themselves in a wireless ad-hoc network. At strategic locations RFID readers are deployed to identify animals in close proximity. The camera network deployed in the zoo is continuous tracking animals in its field of view. By using data fusion from the camera system and the RFID readers we can get semi-continuous tracking of individual animals. The camera network has been running in the zoo for more than one year and about 5 000 hours of video has been captured and recorded. This will give us a very large dataset for offline development and testing of computer vision algorithms for animal detection and tracking.
In this paper we describe our work on building a large scale testbed for wireless video sensor networks. The site for this testbed is a zoo located in north Sweden, Lycksele djurpark. The zoo covers an area of about 47 hectares and is home to more than 400 animals, divided into 30 spieces. This gives us the possibility to build a large scale deployment rich of events to detect. The site is located in nothern Sweden where the winters are dark and cold and the summers have a lot of sunshine. This is an challanging environment for the sensor network deployment where the solar powered sensor nodes needs to be highly adaptive.
In this chapter we will describe our work to set up a large scale wireless visual sensor network in a Swedish zoo. It is located close to the Arctic Circle making the environment very hard for this type of deployment. The goal is to make the zoo digitally enhanced, leading to a more attractive and interactive zoo. To reach this goal the sensed data will be processed and semantic information will be used to support interaction design, which is a key component to provide a new type of experience for the visitors. In this chapter we will describe our research work related to the various aspects of a digital zoo
Knowledge about the indoor occupancy is one of the important sources of information to design smart buildings. In some applications, the number of occupants in each zone is required. However, there are many challenges such as user privacy, communication limit, and sensor’s computational capability in development of the occupancy monitoring systems. In this work, a people flow counting algorithm has been developed which uses low-resolution thermal images to avoid any privacy concern. Moreover, the proposed scheme is designed to be applicable for wireless sensor networks based on the internet-of-things platform. Simple low-complexity image processing techniques are considered to detect possible objects in sensor’s field of view. To tackle the noisy detection measurements, a multi-Bernoulli target tracking approach is used to track and finally to count the number of people passing the area of interest in different directions. Based on the sensor node’s processing capability, one can consider either a centralized or a full in situ people flow counting system. By performing the tracking part either in sensor node or in a fusion center, there would be a trade off between the computational complexity and the transmission rate. Therefore, the developed system can be performed in a wide range of applications with different processing and transmission constraints. The accuracy and robustness of the proposed method are also evaluated with real measurements from different conducted trials and open-source dataset.
There is a need for reliable and efficient methods for monitoring the activity and social behaviour in cows, in order to optimise management in modern dairy farms. This research presents an embedded system that could track individual cows using Ultra-wideband technology. At the same time, social interactions between individuals around the feeding area were analysed with a computer vision module. Detections of the dairy cows' negative and positive interactions were performed on foreground video stream using a Long-term Recurrent Convolution Networks model. The sensor fusion system was implemented and tested on seven dairy cows during 45 days in an experimental dairy farm. The system performance was evaluated at the feeding area. The real-time locating system based on Ultra-wideband technology reached an accuracy with mean error 0.39 m and standard deviation 0.62 m. The accuracy of detecting the affiliative and agonistic social interactions reached 93.2%. This study demonstrates a potential system for monitoring social interactions between dairy cows.
This paper purposes an application based on video supervision systems in the zoo for human animal computer interaction. Bear-Watcher system covers the entire process from collecting animal's visual data, analyzing their movement and behavior, and presenting them to user interface for tourism and animal welfare. With the interaction between the users and animal movement information, the system gives the tourist more digital, more available, more involved experience. In the meanwhile, zoo keepers get reliable, accurate, cost-effective way to take care of animals.
The growing interest of animal welfare is prompted amongst other by understanding basic behavioural need of the animals. The aim of this study was to develop a system that automatically generates animal activity data. Therefore, a computer vision-based system for detecting sheep standing and lying behaviour was proposed. The system was composed of a multi-camera video recording system and a software module which can detect sheep standing/ lying behaviour by using the depth video stream and infrared video stream. Assessment of the detection results were carried out by comparison with the results by observation. The sensitivity of the system achieved for detecting sheep standing and lying was 96.4% and 94.16% respectively. The proposed system was able to compute sheep behaviour and the real-time detection can be achieved. The system can increase the convenience for animal behaviour studies and monitoring of animal welfare in the production environment.
This paper proposes a consumer-oriented design of Interaction System applied in a digital zoo. In order to introduce a new experience of visiting zoos, a series of interaction interfaces and applications is designed based on the web surfing. The applications can be located anywhere has Internet connection, used by visitors both in and out of the zoo. In the meantime, zoo staffs can use the system implement to manage the zoo more efficiently on both computer and smart phone. The digital zoo, as the showcase of the interaction system, employed the technology that combine radio frequency identification (RFID), wireless camera sensor network and computer vision system for collecting and processing information in a reality zoo. The Interaction System for digital zoo enhances effective interaction behavior between human-animals, human-human, and management over animals. The design is based on the Digital Djurpark Porject with current deployment a multimedia sensor network for human animal machine interaction. We have evaluated the effect of interaction model in field experiments.
The growing interest in precision livestock farming is prompted by a desire to understand the basic behavioural needs of the animals and optimize the contribution of each animal. The aim of this study was to develop a system that automatically generated individual animal behaviour and localization data in sheep. A sensor-fusion-system tracking individual sheep position and detecting sheep standing/lying behaviour was proposed. The mean error and standard deviation of sheep position performed by the ultra-wideband location system was 0.357 +/- 0.254 m, and the sensitivity of the sheep standing and lying detection performed by infrared radiation cameras and three-dimenional computer vision technology were 98.16% and 100%, respectively. The proposed system was able to generate individual animal activity reports and the real-time detection was achieved. The system can increase the convenience for animal behaviour studies and monitoring of animal welfare in the production environment.
In this paper we describe the recent development of a low- bandwidth wireless camera sensor network. We propose a simple, yet effective, network architecture which allows multiple cameras to be connected to the network and synchronize their communication schedules. Image compression of greater than 90% is performed at each node running on a local DSP coprocessor, resulting in nodes using 1/8th the energy compared to streaming uncompressed images. We briefly introduce the Fleck wireless node and the DSP/camera sensor, and then outline the network architecture and compression algorithm. The system is able to stream color QVGA images over the network to a base station at up to 2 frames per second.