Search

The growing trend of IT technologies has continued at a faster pace in recent decades. The efforts of experts in this field have always been reducing the problems and challenges existing in urban communities and improving the quality of citizens' lives. They have concentrated on using the artificial intelligence and Internet of Things in a way which leads to maximize self-actualization of citizens. Among these technologies, IoT has played a significant role. Since it can improve the urban infrastructures, and also can be implemented in the scale of home facilities and equipment, can improve the quality of life in smart homes. However, it seems that the implementation of smart residential buildings in the context of smart cities is not simple as been defined in theory and may be accompanied by challenges. In this paper, an attempt has been made to evaluate the environmental factors affecting this field by SWOT analysis tool in a case study in cities of Mazandaran Province in Iran. As a result, strategy and tactics to emphasize strengths, to make the most of existing opportunities, to eliminate the weaknesses, and to reduce the risk of perceived threats, have been identified and been introduced. Based on the results, OS strategy should be held to obtain the most valuable goals of a smart city; since the points of opportunities and strengths are relatively more than others. [ABSTRACT FROM AUTHOR]

Potatoes are the fourth most important crop for human consumption. In the 18 century, potatoes saved the European population from starvation, and since then, it has become one of the primary crops cultivated in countries such as Spain, France, Germany, Ukraine and the United Kingdom. Potato production worldwide reached 368.8 million tonnes in 2019, 371.1 million tonnes in 2020, and 376.1 million tonnes in 2021, with production expected to grow alongside the worldwide population. However, the agricultural sector is currently suffering from urbanization. With the next generation of farmers relocating to cities, there is a diminishing and ageing agricultural workforce. Consequently, farms urgently need innovation, particularly from a technology perspective. As a result, this work is focused on reviewing the worldwide developments in potato harvesting, with an emphasis on mechatronics, the use of intelligent systems and the opportunities that arise from applications utilising the Internet of Things (IoT). Our work covers worldwide scientific publications in the last five years, sustained by public data made available from different governments. We end our review by providing a discussion on the future trends derived from our analysis. [ABSTRACT FROM AUTHOR]

Nowadays, we are observing a rapid development of UAV-based monitoring systems, which are faced with more and more new tasks, such as high temporal resolution and high spatial resolution of measurements, or Artificial Intelligence on board. This paper presents the open universal framework intended for fast prototyping or building a short series of specialized flying monitoring systems able to work in urban and industrial areas. The proposed framework combines mobility of UAV with IoT measurements and full-stack WebRTC communications. WebRTC offers simultaneous transmission of both a real-time video stream and the flow of data coming from sensors, and ensures a kind of protection of data flow, which leads to preserving its near-real-time character and enables contextual communication. Addition of the AI accelerator hardware makes this system AI-ready, i.e., the IoT communication hub, which is the air component of our system, is able to perform tasks of AI-supported computing. The exemplary prototype of this system was evaluated in terms of the ability to work with fast-response sensors, the ability to work with high temporal and high spatial resolutions, video information in poor visibility conditions and AI-readiness. Results show that prototypes based on the proposed framework are able to meet the challenges of monitoring systems in smart cities and industrial areas. [ABSTRACT FROM AUTHOR]

In the past few years, privacy concerns have grown, making the financial models of businesses more vulnerable to attack. In many cases, it is hard to emphasize the importance of monitoring things in real-time with data from Internet of Things (IoT) devices. The people who make the IoT devices and those who use them face big problems when they try to use Artificial Intelligence (AI) techniques in real-world applications, where data must be collected and processed at a central location. Federated learning (FL) has made a decentralized, cooperative AI system that can be used by many IoT apps that use AI. It is possible because it can train AI on IoT devices that are spread out and do not need to share data. FL allows local models to be trained on local data and share their knowledge to improve a global model. Also, shared learning allows models from all over the world to be trained using data from all over the world. This article looks at the IoT in all of its forms, including "smart" businesses, "smart" cities, "smart" transportation, and "smart" healthcare. This study looks at the safety problems that the federated learning with IoT (FL-IoT) area has brought to market. This research is needed to explore because federated learning is a new technique, and a small amount of work is done on challenges faced during integration with IoT. This research also helps in the real world in such applications where encrypted data must be sent from one place to another. Researchers and graduate students are the audience of our article. [ABSTRACT FROM AUTHOR]