Counting Human Flow with Deep Neural Network

Human flow counting has many applications in space management. This study applied channel state information (CSI) available in IEEE 802.11n networks to characterize the flow count. Raw inputs including mean, standard deviation and five-number summary were extracted from windowed CSI data. Due to the large number of raw inputs, stacked denoising autoencoders were used to extract hierarchical features from raw inputs and a final layer of softmax regression was used to model the flow counting problem. It is found that this deep neural network structure beats other popular classification algorithms including random forest, logistic regression, support vector machine and multilayer perceptron in predicting the flow count with attractive speed performance

Exploiting Radio Irregularity in Wireless Networks for Automated People Counting

Wireless devices exist almost everywhere in our daily life. Wireless communications, which is an integral part of wireless devices, suffers from radio irregularity – a phenomenon referring to radio waves being selectively absorbed, reflected or scattered by objects in their paths, e.g., human bodies that comprises liquid, bone and flesh. Radio irregularity is often treated as a major challenge for wireless communication. However, we aim to take advantage of the phenomenon of radio irregularity to provide a cost-effective approach for automated people counting. People counting is extensively used for intelligence-gathering to be used in forecasting, resource allocation and safety-related applications like crowd control. Existing people counting techniques use light, infrared, or thermal energy for human movement detection. However there have major limitations, for example the visible light camera and infrared sensors do not penetrate smoke or obstacles such as wall and furniture. Also, a large deployment of these devices is costly owing to the use of specialized sensors. We propose an automated people counting system using the radio irregularity phenomenon of existing wireless infrastructure with minimal additional hardware and installation costs. This thesis presents an experimental study to demonstrate how radio signal fluctuations arising from radio irregularity can be used to provide a simple low-cost alternative to dedicated sensing systems for indoor automated people counting. Firstly, we study the effect on received signal strength with human motion interference on radio signals. Then we propose and evaluate the performance of three approaches, namely, overcomplete dictionary based pattern recognition (OCPR) approach, probability density approach and standard deviation approach. With high accuracy of motion detection, we then focus on the design of automated people counting system using the proposed detection approach. To differentiate the number of people, we apply discriminant analysis which is a statistical method to perform classification based on independent variables. We validated the proposed people counting system by conducting experiments under both controlled and uncontrolled environments and show that we are able to achieve high accuracy in counting up to five people in groups with no specific formation

CHARACTERIZATION OF RF SIGNAL BEHAVIOR FOR THE USE IN INDOOR HUMAN PRESENCE DETECTION

ABSTRACT This paper presents a method or technique that identifies physical intrusion detection in an indoor environment that is based on received signal strength indicator (RSSI) on radio frequency identification. The objective of this paper is two folds. Firstly, is to characterize the signal behavior in an indoor environment using statistical measures. Secondly, is to identify the existence of a human presence inside a contained environment (e.g., room). The objective is to use simple means like the recorded readings of the received signal strength indicator (RSSI). The characterization was observed during three distinctive time intervals, namely; empty room, with human presence, and transitional period during link crossings. The experiment was repeatedly conducted for 5 minutes to validate the averaged results. In order to emulate real-life environment, experiments were conducted using Zigbee-compliant iris mote XM2110 and MIB510 programming boards with transmitter and receiver antennas, and interfaced using TinyOS software on Linux. Our results show that there are distinctive statistical features that can utilized as flags to classify the three cases stated above, empty room, occupied and link being crossed. These results motivate the design of alarm system to detect human presence using RSSI statistics only

Internet of Underwater Things and Big Marine Data Analytics -- A Comprehensive Survey

The Internet of Underwater Things (IoUT) is an emerging communication ecosystem developed for connecting underwater objects in maritime and underwater environments. The IoUT technology is intricately linked with intelligent boats and ships, smart shores and oceans, automatic marine transportations, positioning and navigation, underwater exploration, disaster prediction and prevention, as well as with intelligent monitoring and security. The IoUT has an influence at various scales ranging from a small scientific observatory, to a midsized harbor, and to covering global oceanic trade. The network architecture of IoUT is intrinsically heterogeneous and should be sufficiently resilient to operate in harsh environments. This creates major challenges in terms of underwater communications, whilst relying on limited energy resources. Additionally, the volume, velocity, and variety of data produced by sensors, hydrophones, and cameras in IoUT is enormous, giving rise to the concept of Big Marine Data (BMD), which has its own processing challenges. Hence, conventional data processing techniques will falter, and bespoke Machine Learning (ML) solutions have to be employed for automatically learning the specific BMD behavior and features facilitating knowledge extraction and decision support. The motivation of this paper is to comprehensively survey the IoUT, BMD, and their synthesis. It also aims for exploring the nexus of BMD with ML. We set out from underwater data collection and then discuss the family of IoUT data communication techniques with an emphasis on the state-of-the-art research challenges. We then review the suite of ML solutions suitable for BMD handling and analytics. We treat the subject deductively from an educational perspective, critically appraising the material surveyed.Comment: 54 pages, 11 figures, 19 tables, IEEE Communications Surveys & Tutorials, peer-reviewed academic journa

Модель функціонування логістичного центру в аеропорту з управлінням ланцюгами поставок

Робота публікується згідно наказу ректора від 29.12.2020 р. №580/од "Про розміщення кваліфікаційних робіт вищої освіти в репозиторії НАУ" . Керівник проекту: Керівник проекту: к. фіз-мат.н., доцент Коновалюк Валентина СтаніславівнаModern development of the economy is impossible without adequate development of the transport network. It functions as a circulatory system in the human body, delivering passengers and cargo throughout the country and abroad. One of the most important components of the transport system is aviation. It is impossible to create and develop a single market of goods and services, to integrate the Ukrainian economy into the world economic system, to improve the quality of life of Ukrainians, to restore the position of Ukraine as one of the full members of the world community without the proactive development of a comprehensive national transport system. Civil aviation has always been a kind of transport for our country, ensuring access to all its territories and connecting with other countries and continents. Improvement of transport technologies and transport equipment is the main direction of increase of labor productivity at transport and the most important condition of guarantee of safety, environmental and economy of transport processes. The organization of passenger transportation by air involves the organization of such technological processes: regulatory and legal support of transportation; transportation sales; service of passengers and their luggage at the airport (service before departure and after); maintenance of aircraft of the airline; servicing passengers on board an aircraft. The basis of the scheme of research of this influence is the model of traffic of passengers and freight traffic and aircraft fleet (in terms of its technical and economic indicators). In the process of implementation of the model, recommendations for the composition of the park are developed, which corresponds to the studied streams to the greatest extent.Сучасний розвиток економіки неможливий без належного розвитку транспортної мережі. Він функціонує як кровоносна система в організмі людини, доставляючи пасажирів та вантажі по всій країні та за кордон. Однією з найважливіших складових транспортної системи є авіація. Неможливо створити і розвинути єдиний ринок товарів і послуг, інтегрувати українську економіку у світову економічну систему, поліпшити якість життя українців, відновити позиції України як одного з повноправних членів світу громади без активного розвитку всеосяжної національної транспортної системи. Цивільна авіація завжди була своєрідним транспортом для нашої країни, забезпечуючи доступ на всі її території та сполучуючи з іншими країнами та континентами. Удосконалення транспортних технологій та транспортного обладнання є основним напрямком підвищення продуктивності праці на транспорті та найважливішою умовою гарантування безпеки, екології та економії транспортних процесів. Організація пасажирських перевезень повітряним транспортом передбачає організацію таких технологічних процесів: нормативно-правове забезпечення перевезень; транспортні продажі; обслуговування пасажирів та їх багажу в аеропорту (обслуговування до вильоту та після); технічне обслуговування літаків авіакомпанії; обслуговування пасажирів на борту літака. В основі схеми дослідження цього впливу лежить модель перевезень пасажирів та вантажних перевезень та авіаційний парк (з точки зору її техніко-економічних показників). У процесі впровадження моделі розробляються рекомендації щодо композиції парку, що найбільшою мірою відповідає досліджуваним потокам

Модель функціонування логістичного центру в аеропорту з управлінням ланцюгами поставок

Робота публікується згідно наказу ректора від 29.12.2020 р. №580/од "Про розміщення кваліфікаційних робіт вищої освіти в репозиторії НАУ" . Керівник проекту: Керівник проекту: к. фіз-мат.н., доцент Коновалюк Валентина СтаніславівнаModern development of the economy is impossible without adequate development of the transport network. It functions as a circulatory system in the human body, delivering passengers and cargo throughout the country and abroad. One of the most important components of the transport system is aviation. It is impossible to create and develop a single market of goods and services, to integrate the Ukrainian economy into the world economic system, to improve the quality of life of Ukrainians, to restore the position of Ukraine as one of the full members of the world community without the proactive development of a comprehensive national transport system. Civil aviation has always been a kind of transport for our country, ensuring access to all its territories and connecting with other countries and continents. Improvement of transport technologies and transport equipment is the main direction of increase of labor productivity at transport and the most important condition of guarantee of safety, environmental and economy of transport processes. The organization of passenger transportation by air involves the organization of such technological processes: regulatory and legal support of transportation; transportation sales; service of passengers and their luggage at the airport (service before departure and after); maintenance of aircraft of the airline; servicing passengers on board an aircraft. The basis of the scheme of research of this influence is the model of traffic of passengers and freight traffic and aircraft fleet (in terms of its technical and economic indicators). In the process of implementation of the model, recommendations for the composition of the park are developed, which corresponds to the studied streams to the greatest extent.Сучасний розвиток економіки неможливий без належного розвитку транспортної мережі. Він функціонує як кровоносна система в організмі людини, доставляючи пасажирів та вантажі по всій країні та за кордон. Однією з найважливіших складових транспортної системи є авіація. Неможливо створити і розвинути єдиний ринок товарів і послуг, інтегрувати українську економіку у світову економічну систему, поліпшити якість життя українців, відновити позиції України як одного з повноправних членів світу громади без активного розвитку всеосяжної національної транспортної системи. Цивільна авіація завжди була своєрідним транспортом для нашої країни, забезпечуючи доступ на всі її території та сполучуючи з іншими країнами та континентами. Удосконалення транспортних технологій та транспортного обладнання є основним напрямком підвищення продуктивності праці на транспорті та найважливішою умовою гарантування безпеки, екології та економії транспортних процесів. Організація пасажирських перевезень повітряним транспортом передбачає організацію таких технологічних процесів: нормативно-правове забезпечення перевезень; транспортні продажі; обслуговування пасажирів та їх багажу в аеропорту (обслуговування до вильоту та після); технічне обслуговування літаків авіакомпанії; обслуговування пасажирів на борту літака. В основі схеми дослідження цього впливу лежить модель перевезень пасажирів та вантажних перевезень та авіаційний парк (з точки зору її техніко-економічних показників). У процесі впровадження моделі розробляються рекомендації щодо композиції парку, що найбільшою мірою відповідає досліджуваним потокам

Investigation on Design and Development Methods for Internet of Things

The thesis work majorly focuses on the development methodologies of the Internet of Things (IoT). A detailed literature survey is presented for the discussion of various challenges in the development of software and design and deployment of hardware. The thesis work deals with the efficient development methodologies for the deployment of IoT system. Efficient hardware and software development reduces the risk of the system bugs and faults. The optimal placement of the IoT devices is the major challenge for the monitoring application. A Qualitative Spatial Reasoning (QSR) and Qualitative Temporal Reasoning (QTR) methodologies are proposed to build software systems. The proposed hybrid methodology includes the features of QSR, QTR, and traditional databased methodologies. The hybrid methodology is proposed to build the software systems and direct them to the specific goal of obtaining outputs inherent to the process. The hybrid methodology includes the support of tools and is detailed, integrated, and fits the general proposal. This methodology repeats the structure of Spatio-temporal reasoning goals. The object-oriented IoT device placement is the major goal of the proposed work. Segmentation and object detection is used for the division of the region into sub-regions. The coverage and connectivity are maintained by the optimal placement of the IoT devices using RCC8 and TPCC algorithms. Over the years, IoT has offered different solutions in all kinds of areas and contexts. The diversity of these challenges makes it hard to grasp the underlying principles of the different solutions and to design an appropriate custom implementation on the IoT space. One of the major objective of the proposed thesis work is to study numerous production-ready IoT offerings, extract recurring proven solution principles, and classify them into spatial patterns. The method of refinement of the goals is employed so that complex challenges are solved by breaking them down into simple and achievable sub-goals. The work deals with the major sub-goals e.g. efficient coverage of the field, connectivity of the IoT devices, Spatio-temporal aggregation of the data, and estimation of spatially connected regions of event detection. We have proposed methods to achieve each sub-goal for all different types of spatial patterns. The spatial patterns developed can be used in ongoing and future research on the IoT to understand the principles of the IoT, which will, in turn, promote the better development of existing and new IoT devices. The next objective is to utilize the IoT network for enterprise architecture (EA) based IoT application. EA defines the structure and operation of an organization to determine the most effective way for it to achieve its objectives. Digital transformation of EA is achieved through analysis, planning, design, and implementation, which interprets enterprise goals into an IoT-enabled enterprise design. A blueprint is necessary for the readying of IT resources that support business services and processes. A systematic approach is proposed for the planning and development of EA for IoT-Applications. The Enterprise Interface (EI) layer is proposed to efficiently categorize the data. The data is categorized based on local and global factors. The clustered data is then utilized by the end-users. A novel four-tier structure is proposed for Enterprise Applications. We analyzed the challenges, contextualized them, and offered solutions and recommendations. The last objective of the thesis work is to develop energy-efficient data consistency method. The data consistency is a challenge for designing energy-efficient medium access control protocol used in IoT. The energy-efficient data consistency method makes the protocol suitable for low, medium, and high data rate applications. The idea of energyefficient data consistency protocol is proposed with data aggregation. The proposed protocol efficiently utilizes the data rate as well as saves energy. The optimal sampling rate selection method is introduced for maintaining the data consistency of continuous and periodic monitoring node in an energy-efficient manner. In the starting phase, the nodes will be classified into event and continuous monitoring nodes. The machine learning based logistic classification method is used for the classification of nodes. The sampling rate of continuous monitoring nodes is optimized during the setup phase by using optimized sampling rate data aggregation algorithm. Furthermore, an energy-efficient time division multiple access (EETDMA) protocol is used for the continuous monitoring on IoT devices, and an energy-efficient bit map assisted (EEBMA) protocol is proposed for the event driven nodes