Survey on wireless technology trade-offs for the industrial internet of things

Aside from vast deployment cost reduction, Industrial Wireless Sensor and Actuator Networks (IWSAN) introduce a new level of industrial connectivity. Wireless connection of sensors and actuators in industrial environments not only enables wireless monitoring and actuation, it also enables coordination of production stages, connecting mobile robots and autonomous transport vehicles, as well as localization and tracking of assets. All these opportunities already inspired the development of many wireless technologies in an effort to fully enable Industry 4.0. However, different technologies significantly differ in performance and capabilities, none being capable of supporting all industrial use cases. When designing a network solution, one must be aware of the capabilities and the trade-offs that prospective technologies have. This paper evaluates the technologies potentially suitable for IWSAN solutions covering an entire industrial site with limited infrastructure cost and discusses their trade-offs in an effort to provide information for choosing the most suitable technology for the use case of interest. The comparative discussion presented in this paper aims to enable engineers to choose the most suitable wireless technology for their specific IWSAN deployment

Passive round-trip-time positioning in dense ieee 802.11 networks

The search for a unique and globally available location solution has attracted researchers for a long time. However, a solution for indoor scenarios, where high accuracy is needed, and Global Positioning System (GPS) is not available, has not been found yet. Despite the number of proposals in the literature, some require too long a calibration time for constructing the fingerprinting map, some rely on the periodic broadcast of positioning information that may downgrade the data communication channel, while others require specific hardware components that are not expected to be carried on commercial off-the-shelf (COTS) wireless devices. The scalability of the location solution is another key parameter for next-generation internet of things (IoT) and 5G scenarios. A passive solution for indoor positioning of WiFi devices is first introduced here, which merges a time-difference of arrival (TDOA) algorithm with the novel fine time measurements (FTM) introduced in IEEE 802.11mc. A proof of concept of the WiFi passive TDOA algorithm is detailed in this paper, together with a thorough discussion on the requirements of the proposed algorithmThis work was funded by the Spanish Government and European Regional Development Fund (ERDF) through Comisión Interministerial de Ciencia y Tecnología (CICYT) under Project PGC2018-099945-B-I00.Peer ReviewedPostprint (published version

Feeding rates of malaria vectors from a prototype attractive sugar bait station in Western Province, Zambia: results of an entomological validation study

Background: Attractive targeted sugar bait (ATSB) stations are a promising new approach to malaria vector control that could compliment current tools by exploiting the natural sugar feeding behaviors of mosquitoes. Recent proof of concept work with a prototype ATSB® Sarabi Bait Station (Westham Co., Hod-Hasharon, Israel) has demonstrated high feeding rates and significant reductions in vector density, human biting rate, and overall entomological inoculation rate for Anopheles gambiae sensu lato (s.l.) in the tropical savannah of western Mali. The study reported here was conducted in the more temperate, rainier region of Western Province, Zambia and was designed to confirm the primary vector species in region and to estimate corresponding rates of feeding from prototype attractive sugar bait (ASB) Sarabi Bait Stations. Methods: The product evaluated was the Sarabi v1.1.1 ASB station, which did not include insecticide but did include 0.8% uranine as a dye allowing for the detection, using UV fluorescence light microscopy, of mosquitoes that have acquired a sugar meal from the ASB. A two-phase, crossover study design was conducted in 10 village-based clusters in Western Province, Zambia. One study arm initially received 2 ASB stations per eligible structure while the other initially received 3. Primary mosquito sampling occurred via indoor and outdoor CDC Miniature UV Light Trap collection from March 01 through April 09, 2021 (Phase 1) and from April 19 to May 28, 2021 (Phase 2). Results: The dominant vector in the study area is Anopheles funestus s.l., which was the most abundant species group collected (31% of all Anophelines; 45,038/144,5550), had the highest sporozoite rate (3.16%; 66 positives out of 2,090 tested), and accounted for 94.3% (66/70) of all sporozoite positive specimens. Of those An. funestus specimens further identified to species, 97.2% (2,090/2,150) were An. funestus sensu stricto (s.s.). Anopheles gambiae s.l. (96.8% of which were Anopheles arabiensis) is a likely secondary vector and Anopheles squamosus may play a minor role in transmission. Overall, 21.6% (9,218/42,587) of An. funestus specimens and 10.4% (201/1,940) of An. gambiae specimens collected were positive for uranine, translating into an estimated daily feeding rate of 8.9% [7.7–9.9%] for An. funestus (inter-cluster range of 5.5% to 12.7%) and 3.9% [3.3–4.7%] for An. gambiae (inter-cluster range of 1.0–5.2%). Feeding rates were no different among mosquitoes collected indoors or outdoors, or among mosquitoes from clusters with 2 or 3 ASBs per eligible structure. Similarly, there were no correlations observed between feeding rates and the average number of ASB stations per hectare or with weekly rainfall amounts. Conclusions: Anopheles funestus and An. gambiae vector populations in Western Province, Zambia readily fed from the prototype Sarabi v1.1.1 ASB sugar bait station. Observed feeding rates are in line with those thought to be required for ATSB stations to achieve reductions in malaria transmission when used in combination with conventional control methods (IRS or LLIN). These results supported the decision to implement a large-scale, epidemiological cluster randomized controlled trial of ATSB in Zambia, deploying 2 ATSB stations per eligible structure

Differential Recurrent Neural Networks for Action Recognition

The long short-term memory (LSTM) neural network is capable of processing complex sequential information since it utilizes special gating schemes for learning representations from long input sequences. It has the potential to model any sequential time-series data, where the current hidden state has to be considered in the context of the past hidden states. This property makes LSTM an ideal choice to learn the complex dynamics of various actions. Unfortunately, the conventional LSTMs do not consider the impact of spatio-temporal dynamics corresponding to the given salient motion patterns, when they gate the information that ought to be memorized through time. To address this problem, we propose a differential gating scheme for the LSTM neural network, which emphasizes on the change in information gain caused by the salient motions between the successive frames. This change in information gain is quantified by Derivative of States (DoS), and thus the proposed LSTM model is termed as differential Recurrent Neural Network (dRNN). We demonstrate the effectiveness of the proposed model by automatically recognizing actions from the real-world 2D and 3D human action datasets. Our study is one of the first works towards demonstrating the potential of learning complex time-series representations via high-order derivatives of states

Map matching by using inertial sensors: literature review

This literature review aims to clarify what is known about map matching by using inertial sensors and what are the requirements for map matching, inertial sensors, placement and possible complementary position technology. The target is to develop a wearable location system that can position itself within a complex construction environment automatically with the aid of an accurate building model. The wearable location system should work on a tablet computer which is running an augmented reality (AR) solution and is capable of track and visualize 3D-CAD models in real environment. The wearable location system is needed to support the system in initialization of the accurate camera pose calculation and automatically finding the right location in the 3D-CAD model. One type of sensor which does seem applicable to people tracking is inertial measurement unit (IMU). The IMU sensors in aerospace applications, based on laser based gyroscopes, are big but provide a very accurate position estimation with a limited drift. Small and light units such as those based on Micro-Electro-Mechanical (MEMS) sensors are becoming very popular, but they have a significant bias and therefore suffer from large drifts and require method for calibration like map matching. The system requires very little fixed infrastructure, the monetary cost is proportional to the number of users, rather than to the coverage area as is the case for traditional absolute indoor location systems.Siirretty Doriast

TRECVID 2008 - goals, tasks, data, evaluation mechanisms and metrics

The TREC Video Retrieval Evaluation (TRECVID) 2008 is a TREC-style video analysis and retrieval evaluation, the goal of which remains to promote progress in content-based exploitation of digital video via open, metrics-based evaluation. Over the last 7 years this effort has yielded a better understanding of how systems can effectively accomplish such processing and how one can reliably benchmark their performance. In 2008, 77 teams (see Table 1) from various research organizations --- 24 from Asia, 39 from Europe, 13 from North America, and 1 from Australia --- participated in one or more of five tasks: high-level feature extraction, search (fully automatic, manually assisted, or interactive), pre-production video (rushes) summarization, copy detection, or surveillance event detection. The copy detection and surveillance event detection tasks are being run for the first time in TRECVID. This paper presents an overview of TRECVid in 2008

Hybridisation of GNSS with other wireless/sensors technologies onboard smartphones to offer seamless outdoors-indoors positioning for LBS applications

Location-based services (LBS) are becoming an important feature on today’s smartphones (SPs) and tablets. Likewise, SPs include many wireless/sensors technologies such as: global navigation satellite system (GNSS), cellular, wireless fidelity (WiFi), Bluetooth (BT) and inertial-sensors that increased the breadth and complexity of such services. One of the main demand of LBS users is always/seamless positioning service. However, no single onboard SPs technology can seamlessly provide location information from outdoors into indoors. In addition, the required location accuracy can be varied to support multiple LBS applications. This is mainly due to each of these onboard wireless/sensors technologies has its own capabilities and limitations. For example, when outdoors GNSS receivers on SPs can locate the user to within few meters and supply accurate time to within few nanoseconds (e.g. ± 6 nanoseconds). However, when SPs enter into indoors this capability would be lost. In another vain, the other onboard wireless/sensors technologies can show better SP positioning accuracy, but based on some pre-defined knowledge and pre-installed infrastructure. Therefore, to overcome such limitations, hybrid measurements of these wireless/sensors technologies into a positioning system can be a possible solution to offer seamless localisation service and to improve location accuracy. This thesis aims to investigate/design/implement solutions that shall offer seamless/accurate SPs positioning and at lower cost than the current solutions. This thesis proposes three novel SPs localisation schemes including WAPs synchronisation/localisation scheme, SILS and UNILS. The schemes are based on hybridising GNSS with WiFi, BT and inertial-sensors measurements using combined localisation techniques including time-of-arrival (TOA) and dead-reckoning (DR). The first scheme is to synchronise and to define location of WAPs via outdoors-SPs’ fixed location/time information to help indoors localisation. SILS is to help locate any SP seamlessly as it goes from outdoors to indoors using measurements of GNSS, synched/located WAPs and BT-connectivity signals between groups of cooperated SPs in the vicinity. UNILS is to integrate onboard inertial-sensors’ readings into the SILS to provide seamless SPs positioning even in deep indoors, i.e. when the signals of WAPs or BT-anchors are considered not able to be used. Results, obtained from the OPNET simulations for various SPs network size and indoors/outdoors combinations scenarios, show that the schemes can provide seamless and locate indoors-SPs under 1 meter in near-indoors, 2-meters can be achieved when locating SPs at indoors (using SILS), while accuracy of around 3-meters can be achieved when locating SPs at various deep indoors situations without any constraint (using UNILS). The end of this thesis identifies possible future work to implement the proposed schemes on SPs and to achieve more accurate indoors SPs’ location

Prioritizing Content of Interest in Multimedia Data Compression

Image and video compression techniques make data transmission and storage in digital multimedia systems more efficient and feasible for the system's limited storage and bandwidth. Many generic image and video compression techniques such as JPEG and H.264/AVC have been standardized and are now widely adopted. Despite their great success, we observe that these standard compression techniques are not the best solution for data compression in special types of multimedia systems such as microscopy videos and low-power wireless broadcast systems. In these application-specific systems where the content of interest in the multimedia data is known and well-defined, we should re-think the design of a data compression pipeline. We hypothesize that by identifying and prioritizing multimedia data's content of interest, new compression methods can be invented that are far more effective than standard techniques. In this dissertation, a set of new data compression methods based on the idea of prioritizing the content of interest has been proposed for three different kinds of multimedia systems. I will show that the key to designing efficient compression techniques in these three cases is to prioritize the content of interest in the data. The definition of the content of interest of multimedia data depends on the application. First, I show that for microscopy videos, the content of interest is defined as the spatial regions in the video frame with pixels that don't only contain noise. Keeping data in those regions with high quality and throwing out other information yields to a novel microscopy video compression technique. Second, I show that for a Bluetooth low energy beacon based system, practical multimedia data storage and transmission is possible by prioritizing content of interest. I designed custom image compression techniques that preserve edges in a binary image, or foreground regions of a color image of indoor or outdoor objects. Last, I present a new indoor Bluetooth low energy beacon based augmented reality system that integrates a 3D moving object compression method that prioritizes the content of interest.Doctor of Philosoph

딥러닝 기반 가속도 및 자이로 센서 데이터 활용 낙상감지 방법

학위논문(석사) -- 서울대학교대학원 : 공학전문대학원 응용공학과, 2022.2. 조성준.As the world enters a super-aged society, fall accidents of elderly people are significantly increasing. These fall accidents, if not detected in time, may lead to serious consequences such as death in the worst cases. Therefore, when a fall accident occurs, it is necessary to establish a system for immediately detection. Among various methods for detecting falls, a device that is easy to wear and can be applied indoors and outdoors is devised. This study aims to develop a model that measures people movement using wearable-based accelerometer sensors and gyro sensors, analyzes acceleration and angular velocity, and classifies whether a fall occurs. In order to obtain data, an experiment was conducted in which 12 ADL movements and 4 Fall movements were repeatedly performed while the subjects were wearing a wearable device. ADL movements include sitting, standing, and walking, and the Fall movement consisting of falling forward and falling backward. In order to detect falls and non-falling, LSTM model of the Recurrent Neural Network (RNN) is used. The model was advanced through a data preprocessing and fine-tuning method applied to the input value of the LSTM model that determines whether to fall or not. In the experimental environment, the fall detection accuracy of the model is 99.91%, which is intended to determine the validity of fall detection from the perspective of deep learning.전 세계가 초고령화 사회로 진입함에 따라 노인 낙상 사고가 크게 증가하고 있다. 이러한 낙상 사고는 제때 감지되지 않을 경우 최악의 경우 사망까지 이를 수 있다. 그러므로 낙상이 발생할 경우 즉시 감지할 수 있는 시스템이 요구된다. 낙상을 발견하기 위한 여러 가지 방법 중에서 착용이 쉽고 실내외에서 적용이 가능한 웨어러블(Wearable) 장치의 형태를 고안한다. 본 연구는 웨어러블 기반 가속도 센서와 자이로 센서를 활용하여 착용자의 움직임을 측정하고, 가속도 및 각속도 값을 분석하여 낙상 발생 여부를 분류하는 모델을 개발하고자 한다. 데이터를 획득하기 위하여 피실험자에게 웨어러블 장치를 착용한 상태로 12가지 일상생활동작과 4가지 낙상동작을 반복적으로 실시하는 실험을 수행하였다. 일상생활동작은 앉기, 서있기, 걷기 등이 있고, 낙상동작은 앞으로 넘어지는 동작, 뒤로 넘어지는 동작 등으로 구성된 데이터를 확보하였다. 낙상과 비낙상 여부를 검출하기 위하여 딥러닝 알고리즘 모델 중 순환 신경망(Recurrent Neural Network, RNN) 계열의 LSTM을 활용한다. 낙상 여부를 판단하는 LSTM 모델에 적용되는 데이터의 전처리 및 미세조정(Fine-Tuning)을 통해서 모델을 고도화 하였다. 실험 환경에서 모델의 낙상감지 정확도(Accuracy)는 99.91%로 심층학습 관점에서 낙상 검출의 타당성을 판단하고자 한다.I. Introduction 1 1.1 Research Background and Objective 1 1.2 Research Scope and Structure of Paper 3 II. Background Knowledge and Related Research 5 2.1 Falls 5 2.2 Fall Detection Techniques 6 2.3 Machine Learning 8 2.4 Recurrent Neural Networks and LSTM 9 III. Methods 13 3.1 Measurement Methods and Devices 13 3.2 Definition of Falls and Daily Living Activities 15 3.3 Development of Fall Detection Model 19 3.4 Performance Evaluation Metrics 21 IV. Results 23 4.1 Data Collection 23 4.2 Data Preprocessing 26 4.3 Model Fine-Tuning 34 4.4 Performance and Results Analysis 36 V. Conclusion 39 5.1 Discussion 39 5.2 Limitations 39 5.3 Future Works 40 Bibliography 43 Abstract in Korean 45석