Abstraction, Bare Life, and Counternarratives of Mobility in the Refugee Films of Richard Mosse and Ai Weiwei, Incoming and Human Flow

This chapter explores the unprecedented formal experiments of Richard Mosse and Ai Weiwei in their attempts to capture the signature global event of our time, the mass movements of refugees and immigrants across geopolitical boundaries. In Mosse’s Incoming, a thermal camera registers the heat emanating from human bodies from some 30 miles away, providing images of refugees in lifeboats, transport trucks, and refugee camps that are both other-worldly, almost mutant in their strangeness, and deeply moving—images that rivet the gaze. In Ai Weiwei’s Human Flow, drone cameras render the vast scale of human displacement around the world—a view from above is interspersed with the close witnessing of cell phone video, using the visual language of spontaneous documentation in counterpoint with a technology associated with military surveillance. In both films, Giorgio Agamben’s concept of “bare life” is articulated within an advanced optical and technological framework that brings new critical questions into view.

Detection of Possible COVID-19 Cases using Thermal Imaging and a DRONE

In December 2019, a series of cases of pneumonia caused by SARS-CoV-2 were identified in Wuhan (China), which was declared by the WHO as a pandemic on March 11th , 2020, because it caused enormous problems for the global public health due to its rapid expansion. In Peru it was only on March 6th , 2020, that the first case of COVID-19 was reported, therefore, the government took some measures to control the spread of the virus. A biosafety measure that is frequently used is taking the temperature with an infrared thermometer, which is not well seen by some specialists due to the error it has, therefore, it would not represent a safe measurement, as other measurement systems do. . In view of this problem, in this article a thermal image processing system was carried out to detect possible cases of patients with COVID-19, in such a way that the system performs a more accurate measurement of body temperature and can be implemented in any place, where this measurement is intended to be carried out, helping to combat the spread of the virus that currently continues to affect many people. Through the development of the system, tests were conducted with various people, obtaining a more accurate measurement of body temperature with an efficiency of 95% at 1 m between the drone and the person, in such a way that if it presents a body temperature above 37°C could be infected with COVID-19. Keywords-- Thermal camera, COVID-19, Drone, MATLAB, WHO, Image processing

Multiple Linear Regression and Deep Learning in Body Temperature Detection and Mask Detection

In this new normal era, many activities began to operate again, such as offices, malls, etc. This creates a potential mass crowd. The public must follow health protocols as recommended by the government, including wearing masks and checking the temperature to anticipate the spread of the coronavirus. This study tested a tool that included image processing and artificial intelligence to help implement health protocols as recommended by the government. This tool connects Raspberry PI, Thermal Camera (amg8833), Pi Camera, an ultrasonic sensor with Multiple Linear Regression and Deep Learning algorithms. The purpose of this tool is to detect body temperature and detect the use of masks. The system will check on the pi camera frame whether the person is wearing a mask or not. The system is trained using the Deep Learning method to detect the use of masks. The system will check the temperature of the human body and the distance between humans and the tool. Temperature and distance data are entered in multiple linear regression formulas to get more accurate results. The processed results of the system will be displayed on the monitor screen if detected using a mask and the normal temperature will be green and if it is not detected it will be red and give a warning sound. The data is sent to the server and displayed via the web. We found that this tool succeeded in detecting body temperature within a distance of 1 to 3 meters with an accuracy of 99.49%, detecting people using masks with an accuracy of 94.71%, and detecting people not wearing masks with an accuracy of 97.7%.

COVID surveillance robot: Monitoring social distancing constraints in indoor scenarios

Observing social/physical distancing norms between humans has become an indispensable precaution to slow down the transmission of COVID-19. We present a novel method to automatically detect pairs of humans in a crowded scenario who are not maintaining social distancing, i.e. about 2 meters of space between them using an autonomous mobile robot and existing CCTV (Closed-Circuit TeleVision) cameras. The robot is equipped with commodity sensors, namely an RGB-D (Red Green Blue—Depth) camera and a 2-D lidar to detect social distancing breaches within their sensing range and navigate towards the location of the breach. Moreover, it discreetly alerts the relevant people to move apart by using a mounted display. In addition, we also equip the robot with a thermal camera that transmits thermal images to security/healthcare personnel who monitors COVID symptoms such as a fever. In indoor scenarios, we integrate the mobile robot setup with a static wall-mounted CCTV camera to further improve the number of social distancing breaches detected, accurately pursuing walking groups of people etc. We highlight the performance benefits of our robot + CCTV approach in different static and dynamic indoor scenarios.

ANALISIS KEMAMPUAN SELF HEALING PADA LAPIS ASPAL BETON DENGAN LIMBAH BUBUTAN BAJA SEBAGAI BAHAN TAMBAH

Steel waste is waste generated from a large or small amount of steel production process. The results of steel waste disposal can pollute the environment if not done a good treatment and countermeasure so that it has value benefits. This study uses steel lathe waste additives to determine the self-healing ability of asphalt in the AC-WC mixture. Steel lathe waste used with varying degrees of steel lathe 0%, 0,25%, 0,5%, 0,75%, 1% and asphalt content used by 5,5%. After obtaining the data used in the study, samples were made for asphalt mixtures with varying degrees. Then the finished sample is divided into 4 parts to be tested for temperature rise on each steel lathe mixture using a thermal camera. And tested using a threepoint bending test to determine the ability of asphalt selfhealing in the AC-WC mixture that occurs for 5 cycles with a heating duration of 20 seconds, 40 seconds, 60 seconds. From the results of the research on the content of a mixture of 0% steel lathe proved the sample can do self-healing but the results obtained are not as good as when using variations in the added ingredients of steel fiber mixture 0,25%, 0,5%, 0,75% and 1%. ABSTRAKLimbah baja adalah buangan yang dihasilkan dari suatu proses produksi baja baik dalam jumlah yang besar atau sedikit. Hasil buangan limbah baja dapat mecemari lingkungan apabila tidak dilakukan pengolahan dan penanggulangan yang baik sehingga memiliki nilai manfaat. Penelitian ini menggunakan bahan tambahan limbah bubutan baja untuk dapat mengetahui kemampuan self healing aspal pada campuran AC-WC. Limbah bubutan baja yang digunakan dengan kadar variasi bubutan baja 0%, 0,25%, 0,5%, 0,75%, 1% dan kadar aspal yang dipakai sebesar 5,5%. Setelah didapatkan data yang dipakai dalam penelitian dilakukan pembuatan sampel terhadap campuran aspal dengan variasi kadar. Kemudian sampel yang telah jadi di belah menjadi 4 bagian untuk diuji kenaikan temperatur pada setiap campuran bubutan baja dengan menggunakan kamera thermal. Serta diuji dengan menggunakan alat threepoint bending test untuk mengetahui kemampuan selfhealing aspal pada campuran AC-WC yang terjadi selama 5 siklus dengan durasi pemanasan 20 detik, 40 detik, 60 detik. Dari hasil penelitian pada kadar campuran bubutan baja 0% terbukti sampel dapat melakukan self healing tetapi hasil yang didapatkan tidak sebaik ketika menggunakan variasi bahan tambah campuran serat baja 0,25%, 0,5%, 0,75% dan 1%.

Detection of “Legbreaker” Antipersonnel Landmines by Analysis of Aerial Thermographic Images of the Soil

An automatic detection methodology for “legbreaker” Antipersonnel Landmines (APL) was developed based on digital image processing techniques and pattern recognition, applied to thermal images acquired by means of an Unmanned Aerial Vehicle (UAV) equipped with a thermal camera. The images were acquired from the inspection of a natural terrain with sparse vegetation and under uncontrolled conditions, in which prototypes of “legbreaker” APL were buried at different depths. Remarkable results were obtained using a Multilayer Perceptron (MLP) classifier, reaching a 97.1% success rate in detecting areas with the presence of these artifacts.

Implementation of Thermal Camera for Non-Contact Physiological Measurement: A Systematic Review

Non-contact physiological measurements based on image sensors have developed rapidly in recent years. Among them, thermal cameras have the advantage of measuring temperature in the environment without light and have potential to develop physiological measurement applications. Various studies have used thermal camera to measure the physiological signals such as respiratory rate, heart rate, and body temperature. In this paper, we provided a general overview of the existing studies by examining the physiological signals of measurement, the used platforms, the thermal camera models and specifications, the use of camera fusion, the image and signal processing step (including the algorithms and tools used), and the performance evaluation. The advantages and challenges of thermal camera-based physiological measurement were also discussed. Several suggestions and prospects such as healthcare applications, machine learning, multi-parameter, and image fusion, have been proposed to improve the physiological measurement of thermal camera in the future.

Noninvasive Passenger Detection Comparison Using Thermal Imager and IP Cameras

Many modern vehicles today are equipped with an on-board e-call system that can send information about the number of passengers in the event of an accident. However, in case of fire or other major danger in a road tunnel, it is very important for rescue services to know not only the number of passengers in a given vehicle that has an accident and called help via e-call but how many people are in the tunnel in total. This paper deals with the issue of passenger detection and counting using the TPH3008-S Thermal camera and the VIVOTEK IP7361 IP Cameras noninvasively, i.e., the cameras are placed outside the vehicle. These cameras have their limitations; therefore, we investigated how to improve conditions and how to make detection better for future work. The main goal of this article is to summarize the achieved results and possibilities of improvement of the proposed system by adding other sensors and systems that would improve the final score of passenger detection. The experimental results demonstrate that our approach has to be modified and we have to add additional sensors or change methods to achieve more promising results. The results, findings and conclusions might be later used in tunnels and highways and also be applied in telematics and lead to better, safer road transport and improvement of existing tunnel systems sustainability by utilizing resources in a smarter way.