Deep Thermal Imaging: Proximate Material Type Recognition in the Wild through Deep Learning of Spatial Surface Temperature Patterns

We introduce Deep Thermal Imaging, a new approach for close-range automatic recognition of materials to enhance the understanding of people and ubiquitous technologies of their proximal environment. Our approach uses a low-cost mobile thermal camera integrated into a smartphone to capture thermal textures. A deep neural network classifies these textures into material types. This approach works effectively without the need for ambient light sources or direct contact with materials. Furthermore, the use of a deep learning network removes the need to handcraft the set of features for different materials. We evaluated the performance of the system by training it to recognise 32 material types in both indoor and outdoor environments. Our approach produced recognition accuracies above 98% in 14,860 images of 15 indoor materials and above 89% in 26,584 images of 17 outdoor materials. We conclude by discussing its potentials for real-time use in HCI applications and future directions.Comment: Proceedings of the 2018 CHI Conference on Human Factors in Computing System

Averting Robot Eyes

Home robots will cause privacy harms. At the same time, they can provide beneficial services—as long as consumers trust them. This Essay evaluates potential technological solutions that could help home robots keep their promises, avert their eyes, and otherwise mitigate privacy harms. Our goals are to inform regulators of robot-related privacy harms and the available technological tools for mitigating them, and to spur technologists to employ existing tools and develop new ones by articulating principles for avoiding privacy harms. We posit that home robots will raise privacy problems of three basic types: (1) data privacy problems; (2) boundary management problems; and (3) social/relational problems. Technological design can ward off, if not fully prevent, a number of these harms. We propose five principles for home robots and privacy design: data minimization, purpose specifications, use limitations, honest anthropomorphism, and dynamic feedback and participation. We review current research into privacy-sensitive robotics, evaluating what technological solutions are feasible and where the harder problems lie. We close by contemplating legal frameworks that might encourage the implementation of such design, while also recognizing the potential costs of regulation at these early stages of the technology

IoT Resources and Their Practical Application, A Comprehensive Study

The Internet of Things (IoT) has become a paradigm shifter, connecting an enormous number of smart devices and facilitating seamless data exchange for a diverse array of applications. The availability and effective use of the IoT ecosystem's resources are key factors in determining how its practical applications will develop as they mature. The IoT resources and their practical application across several areas are thoroughly explored in this paper. The paper begins by classifying and describing the various sensor types, their applications in various fields, and IoT resources, highlighting their contributions to real-time data collection, processing, and transmission. It then goes on to demonstrate a wide range of real-world uses for these resources, such as smart cities, education, agriculture, business, healthcare, environment monitoring, transportation, and industrial automation. However, utilizing IoT resources effectively is not without difficulties. Critical difficulties such as resource allocation, scalability, security, interoperability, and privacy concerns are identified and discussed in the paper. Furthermore, the paper also highlights future directions and emerging trends in IoT resource management, including edge computing, cloud computing, human machine integration, and compatibility with other systems. These developments aim to increase the dependability of IoT applications in diverse settings and optimize resource allocation. This paper's conclusion highlights the crucial role that IoT resources play in advancing real-world applications across a variety of areas. Researchers, practitioners, policymakers, and other stakeholders may collaborate together to effectively leverage the full potential of IoT resources to build intelligent, effective ecosystems that meet the needs of contemporary society by solving difficulties and utilizing developing trends

Sensory and control system for smart fan

A smart fan is a development of an ordinary fan that consists of several features to help more comfortable and easier life. Ordinary stand fan is operated manually which people has to determine the speed of the fan and the oscillation of the fan is fix at a certain degrees. The smart fan is developed to have a speed regarding to the environment temperature and it will only operate as there is presence of human. Furthermore the fan is designed to oscillate with respect to the human location. To this extend, researches on the temperature controller and human location detection have been done and the system design explained in this report. The working principle of smart fan is interrelated between electromechanical, electronics and control system. The LM35 is used to determine the environment temperature meanwhile the passive infrared is used to determine the presence of human and ultrasonic sensors are used to detect the human location. The system is controlled by microcontroller which making the typical stand fan to be smarter