Parking lot monitoring system using an autonomous quadrotor UAV

The main goal of this thesis is to develop a drone-based parking lot monitoring system using low-cost hardware and open-source software. Similar to wall-mounted surveillance cameras, a drone-based system can monitor parking lots without affecting the flow of traffic while also offering the mobility of patrol vehicles. The Parrot AR Drone 2.0 is the quadrotor drone used in this work due to its modularity and cost efficiency. Video and navigation data (including GPS) are communicated to a host computer using a Wi-Fi connection. The host computer analyzes navigation data using a custom flight control loop to determine control commands to be sent to the drone. A new license plate recognition pipeline is used to identify license plates of vehicles from video received from the drone

Nigeria Paper Currency Serial Number Pattern Recognition System for Crimes Control

Only secured and conducive environment void of robbery, kidnapping, fake currency and all forms of insurgencies will foster production and distribution of goods, investment and saving that enhance national economic growth and development. This is a mirage in a country generally believed and tagged the giant of African; Nigeria. Crime, in whatever name or nomenclature, has a significant negative impact on the welfare and economy prosperities of our society. The urge to get rich promotes Crime like armed robbery, kidnapping for ransom and production of counterfeit banknotes to mention but a few. Innocent people have suffered psychological distress, fear, anger, depression, physical harm, financial loss and in most cases untimely death during the operations by these hoodlums. Banks, Cash-In-Transit Vehicle, and ATM points are often robbed by gangs in search for paper currency. Kidnappers as well demand for paper currency as ransom while some other gangs are involved in the production of counterfeit banknotes so as to enrich themselves no minding the negative effect on the nation’s economy.  The banknotes collected during the operations by the hoodlums are taken to banks. Yet, the banks will not detect or recognize any of these notes which attest to the fact that our system lacks check and balance. The system is very porous without a recourse to this era of technology when machine is trained to do virtually everything for our convenience. Currency as an entity has a unique identification number. The identification number is an alphanumeric currency issuance of about 10 digits comprises two (2) capital letters and eight (8) numbers usually positioned at a strategic location on either front or back of the 5, 10, 20, 50, 100, 200, 500 and 1000 naira notes. It is a reliable and intelligent system developed to track banknotes unique identifiers numbers- serial numbers, in order to control financial related crimes. Keywords: Nigeria Paper Currency Serial Number, Pattern Recognition DOI: 10.7176/IKM/11-3-04 Publication date: April 30th 202

Leveraging a Publish/Subscribe Fog System to Provide Collision Warnings in Vehicular Networks

[EN] Fog computing, an extension of the Cloud Computing paradigm where routers themselves may provide the virtualisation infrastructure, aims at achieving fluidity when distributing in-network functions, in addition to allowing fast and scalable processing, and exchange of information. In this paper we present a fog computing architecture based on a content island which interconnects sets of things to exchange and process data among themselves or with other content islands. We then present a use case that focuses on a smartphone-based forward collision warning application for a connected vehicle scenario. This application makes use of the optical sensor of smartphones to estimate the distance between the device itself and other vehicles in its field of view. The vehicle travelling directly ahead is identified relying on the information from the GPS, camera, and inter-island communication. Warnings are generated at both content islands, if the driver does not maintain a predefined safe distance towards the vehicle ahead. Experiments performed with the application show that with the developed method, we are able to estimate the distance between vehicles, and the inter-island communication has a very low overhead, resulting in improved performance. On comparing our proposed solution based on edge/fog computing with a cloud-based api, it was observed that our solution outperformed the cloud-based api, thus making us optimistic of the utility of the proposed architectureThis work was partially funding by the Ministerio de Ciencia, Innovación y Universidades, Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad, Proyectos I+D+I 2018 , Spain, under Grant RTI2018-096384-B-I00Patra, S.; Manzoni, P.; Tavares De Araujo Cesariny Calafate, CM.; Zamora-Mero, WJ.; Cano, J. (2019). Leveraging a Publish/Subscribe Fog System to Provide Collision Warnings in Vehicular Networks. Sensors. 19(18):1-22. https://doi.org/10.3390/s19183852S1221918Vaquero, L. M., & Rodero-Merino, L. (2014). Finding your Way in the Fog. ACM SIGCOMM Computer Communication Review, 44(5), 27-32. doi:10.1145/2677046.2677052MQTT Version 3.1.1 http://docs.oasis-open.org/mqtt/mqtt/v3.1.1/os/mqtt-v3.1.1-os.docSultana, T., & Wahid, K. A. (2019). Choice of Application Layer Protocols for Next Generation Video Surveillance Using Internet of Video Things. IEEE Access, 7, 41607-41624. doi:10.1109/access.2019.2907525Mehmood, F., Ullah, I., Ahmad, S., & Kim, D. (2019). Object detection mechanism based on deep learning algorithm using embedded IoT devices for smart home appliances control in CoT. Journal of Ambient Intelligence and Humanized Computing. doi:10.1007/s12652-019-01272-8https://tools.ietf.org/html/rfc2616https://tools.ietf.org/html/rfc7252Volvo Official Website https://www.volvocars.com/Chang, B. R., Tsai, H. F., & Young, C.-P. (2010). Intelligent data fusion system for predicting vehicle collision warning using vision/GPS sensing. Expert Systems with Applications, 37(3), 2439-2450. doi:10.1016/j.eswa.2009.07.036Tan, H.-S., & Huang, J. (2006). DGPS-Based Vehicle-to-Vehicle Cooperative Collision Warning: Engineering Feasibility Viewpoints. IEEE Transactions on Intelligent Transportation Systems, 7(4), 415-428. doi:10.1109/tits.2006.883938Gelernter, D. (1985). Generative communication in Linda. ACM Transactions on Programming Languages and Systems, 7(1), 80-112. doi:10.1145/2363.2433Raspberry Pi Official Website https://www.raspberrypi.org/https://tools.ietf.org/html/rfc768Wallace, G. K. (1991). The JPEG still picture compression standard. Communications of the ACM, 34(4), 30-44. doi:10.1145/103085.103089Sauvola, J., & Pietikäinen, M. (2000). Adaptive document image binarization. Pattern Recognition, 33(2), 225-236. doi:10.1016/s0031-3203(99)00055-2Road Safety Authority of Ireland Suggest the Use of Two Second Rule http://www.rotr.ie/Rules_of_the_road.pdfOpenALPR Cloud-API Website https://www.openalpr.com/cloud-api.htmlPatra, S., Calafate, C. T., Cano, J.-C., & Manzoni, P. (2015). An ITS solution providing real-time visual overtaking assistance using smartphones. 2015 IEEE 40th Conference on Local Computer Networks (LCN). doi:10.1109/lcn.2015.736632

Smart environment monitoring through micro unmanned aerial vehicles

In recent years, the improvements of small-scale Unmanned Aerial Vehicles (UAVs) in terms of flight time, automatic control, and remote transmission are promoting the development of a wide range of practical applications. In aerial video surveillance, the monitoring of broad areas still has many challenges due to the achievement of different tasks in real-time, including mosaicking, change detection, and object detection. In this thesis work, a small-scale UAV based vision system to maintain regular surveillance over target areas is proposed. The system works in two modes. The first mode allows to monitor an area of interest by performing several flights. During the first flight, it creates an incremental geo-referenced mosaic of an area of interest and classifies all the known elements (e.g., persons) found on the ground by an improved Faster R-CNN architecture previously trained. In subsequent reconnaissance flights, the system searches for any changes (e.g., disappearance of persons) that may occur in the mosaic by a histogram equalization and RGB-Local Binary Pattern (RGB-LBP) based algorithm. If present, the mosaic is updated. The second mode, allows to perform a real-time classification by using, again, our improved Faster R-CNN model, useful for time-critical operations. Thanks to different design features, the system works in real-time and performs mosaicking and change detection tasks at low-altitude, thus allowing the classification even of small objects. The proposed system was tested by using the whole set of challenging video sequences contained in the UAV Mosaicking and Change Detection (UMCD) dataset and other public datasets. The evaluation of the system by well-known performance metrics has shown remarkable results in terms of mosaic creation and updating, as well as in terms of change detection and object detection

Development of Automatic Digitization of Truck Number in Open Cast Mines Using Microcontroller

Geological condition in mines appears to be extremely complicated and there are many intelligence security problems. Production is falsely transfer by the unauthorized truck from mine pits also at loading point. It also lifted in wrong ways by malfunctioning of the truck weight in Weigh Bridge. Mining organizations are under the control of mafia and countless can be added to the mines mafia. An intelligence security system is need to monitor truck number in automatically using image acquisition method, automatic detection, recognition process, communication technology, information technology and microcontroller innovation to understand the working specification of the mining region. Tracking of the number plate from the truck is an important task, which demands intelligent solution. Intelligent surveillance in open casts mine security network using data accession is a prime task that protects the secure production of mines. So automatic truck number recognition technique is used to recognize the registration number of the truck which is used for transferring the mine production as well as track record the amount of the production. It also preserves the mines and thus improving its security. For extraction and recognition of number plate from truck image the system is uses MATLAB software tool. It is assumed that images of the truck have been captured from digital camera. The data acquisition terminal uses the PIC16F877A microcontroller as a core chip for sending data. The data are communicated through USB to TTL converter (RS232) with the main circuit to realize intelligent monitoring. To store the data in permanently it is uses EEPROM chip. Alphanumeric Characters on plate has been extracted and recognized using template images of alphanumeric characters. The proposed system performs the real time data monitoring to recognize the registration number plate of the trucks for getting required important information. It also provides to maintenance the history of data and support access contro

Computer vision reading on stickers and direct part marking on horticultural products : challenges and possible solutions

Traceability of products from production to the consumer has led to a technological advancement in product identification. There has been development from the use of traditional one-dimensional barcodes (EAN-13, Code 128, etc.) to 2D (two-dimensional) barcodes such as QR (Quick Response) and Data Matrix codes. Over the last two decades there has been an increased use of Radio Frequency Identification (RFID) and Direct Part Marking (DPM) using lasers for product identification in agriculture. However, in agriculture there are still considerable challenges to adopting barcodes, RFID and DPM technologies, unlike in industry where these technologies have been very successful. This study was divided into three main objectives. Firstly, determination of the effect of speed, dirt, moisture and bar width on barcode detection was carried out both in the laboratory and a flower producing company, Brandkamp GmbH. This study developed algorithms for automation and detection of Code 128 barcodes under rough production conditions. Secondly, investigations were carried out on the effect of low laser marking energy on barcode size, print growth, colour and contrast on decoding 2D Data Matrix codes printed directly on apples. Three different apple varieties (Golden Delicious, Kanzi and Red Jonaprince) were marked with various levels of energy and different barcode sizes. Image processing using Halcon 11.0.1 (MvTec) was used to evaluate the markings on the apples. Finally, the third objective was to evaluate both algorithms for 1D and 2D barcodes. According to the results, increasing the speed and angle of inclination of the barcode decreased barcode recognition. Also, increasing the dirt on the surface of the barcode resulted in decreasing the successful detection of those barcodes. However, there was 100% detection of the Code 128 barcode at the company’s production speed (0.15 m/s) with the proposed algorithm. Overall, the results from the company showed that the image-based system has a future prospect for automation in horticultural production systems. It overcomes the problem of using laser barcode readers. The results for apples showed that laser energy, barcode size, print growth, type of product, contrast between the markings and the colour of the products, the inertia of the laser system and the days of storage all singularly or in combination with each other influence the readability of laser Data Matrix codes and implementation on apples. There was poor detection of the Data Matrix code on Kanzi and Red Jonaprince due to the poor contrast between the markings on their skins. The proposed algorithm is currently working successfully on Golden Delicious with 100% detection for 10 days using energy 0.108 J mm-2 and a barcode size of 10 × 10 mm2. This shows that there is a future prospect of not only marking barcodes on apples but also on other agricultural products for real time production

Rail Robot for Rail Track Inspection

Railway transportation requires constant inspections and immediate maintenance to ensure public safety. Traditional manual inspections are not only time consuming, but also expensive. In addition, the accuracy of defect detection is also subjected to human expertise and efficiency at the time of inspection. Computing and Robotics offer automated IoT based solutions where robots could be deployed on rail-tracks and hard to reach areas, and controlled from control rooms to provide faster and low-cost inspection. In this thesis, a novel automated system based on robotics and visual inspection is proposed. The system provides local image processing while inspecting and cloud storage of information that consist of images of the defected railway tracks only. The proposed system utilizes state of the art Machine Learning system and applies it on the images obtained from the tracks in order to classify them as normal or suspicious. Such locations are then marked and more careful inspection can be performed by a dedicated operator with very few locations to inspect (as opposed to the full track)

Eyes-Free Vision-Based Scanning of Aligned Barcodes and Information Extraction from Aligned Nutrition Tables

Visually impaired (VI) individuals struggle with grocery shopping and have to rely on either friends, family or grocery store associates for shopping. ShopMobile 2 is a proof-of-concept system that allows VI shoppers to shop independently in a grocery store using only their smartphone. Unlike other assistive shopping systems that use dedicated hardware, this system is a software only solution that relies on fast computer vision algorithms. It consists of three modules - an eyes free barcode scanner, an optical character recognition (OCR) module, and a tele-assistance module. The eyes-free barcode scanner allows VI shoppers to locate and retrieve products by scanning barcodes on shelves and on products. The OCR module allows shoppers to read nutrition facts on products and the tele-assistance module allows them to obtain help from sighted individuals at remote locations. This dissertation discusses, provides implementations of, and presents laboratory and real-world experiments related to all three modules