Applications of Federated Learning in Smart Cities: Recent Advances, Taxonomy, and Open Challenges

Federated learning plays an important role in the process of smart cities. With the development of big data and artificial intelligence, there is a problem of data privacy protection in this process. Federated learning is capable of solving this problem. This paper starts with the current developments of federated learning and its applications in various fields. We conduct a comprehensive investigation. This paper summarize the latest research on the application of federated learning in various fields of smart cities. In-depth understanding of the current development of federated learning from the Internet of Things, transportation, communications, finance, medical and other fields. Before that, we introduce the background, definition and key technologies of federated learning. Further more, we review the key technologies and the latest results. Finally, we discuss the future applications and research directions of federated learning in smart cities

Study of Existing IOT Frameworks for Building Future Building Automation System and Connected Objects

IOT development is unfaltering in India yet with the data framework bolster structure .Govt of India is developing IOT and used through applications. The paper reviews a portion of the current frameworks open for Internet of things. Numerous Big IT Companies have done their part of research and development in the field of IOT., for instance, IBM, Google, GE and IOT stages Amazon . As of now a bundle of various new organizations are using them for IOT applications . In Indian point of view it is to understand that India will be the future for impacting its rural network to Smart splendid urban networks

Internet of Things: Surveys for Measuring Human Activities from Everywhere

The internet of things (IoT), also called internet of all, is a new paradigm that combines several technologies such as computers, the internet, sensors network, radio frequency identification (RFID), communication technology and embedded systems to form a system that links the real worlds with digital worlds. With an increase in the deployment of smart objects, the internet of things should have a significant impact on human life in the near future. To understand the development of the IoT, this paper reviews the current research of the IoT, key technologies, the main applications of the IoT in various fields, and identifies research challenges. A main contribution of this review article is that it summarizes the current state of the IoT technology in several areas, and also the applications of IoT that cause side effects on our environment for monitoring and evaluation of the impact of human activity on the environment around us, and also provided an overview of some of the main challenges and application of IoT. This article presents not only the problems and challenges of IoT, but also solutions that help overcome some of the problems and challenges

Discrete event simulation and virtual reality use in industry: new opportunities and future trends

This paper reviews the area of combined discrete event simulation (DES) and virtual reality (VR) use within industry. While establishing a state of the art for progress in this area, this paper makes the case for VR DES as the vehicle of choice for complex data analysis through interactive simulation models, highlighting both its advantages and current limitations. This paper reviews active research topics such as VR and DES real-time integration, communication protocols, system design considerations, model validation, and applications of VR and DES. While summarizing future research directions for this technology combination, the case is made for smart factory adoption of VR DES as a new platform for scenario testing and decision making. It is put that in order for VR DES to fully meet the visualization requirements of both Industry 4.0 and Industrial Internet visions of digital manufacturing, further research is required in the areas of lower latency image processing, DES delivery as a service, gesture recognition for VR DES interaction, and linkage of DES to real-time data streams and Big Data sets

Federated Learning for Malware Detection in IoT Devices

The Internet of Things (IoT) is penetrating many facets of our daily life with the proliferation of intelligent services and applications empowered by artificial intelligence (AI). Traditionally, AI techniques require centralized data collection and processing that may not be feasible in realistic application scenarios due to the high scalability of modern IoT networks and growing data privacy concerns. Federated Learning (FL) has emerged as a distributed collaborative AI approach that can enable many intelligent IoT applications, by allowing for AI training at distributed IoT devices without the need for data sharing. In this article, we provide a comprehensive survey of the emerging applications of FL in IoT networks, beginning from an introduction to the recent advances in FL and IoT to a discussion of their integration. Particularly, we explore and analyze the potential of FL for enabling a wide range of IoT services, including IoT data sharing, data offloading and caching, attack detection, localization, mobile crowdsensing, and IoT privacy and security. We then provide an extensive survey of the use of FL in various key IoT applications such as smart healthcare, smart transportation, Unmanned Aerial Vehicles (UAVs), smart cities, and smart industry. The important lessons learned from this review of the FL-IoT services and applications are also highlighted. We complete this survey by highlighting the current challenges and possible directions for future research in this booming area

Federated Learning for Malware Detection in IoT Devices

The Internet of Things (IoT) is penetrating many facets of our daily life with the proliferation of intelligent services and applications empowered by artificial intelligence (AI). Traditionally, AI techniques require centralized data collection and processing that may not be feasible in realistic application scenarios due to the high scalability of modern IoT networks and growing data privacy concerns. Federated Learning (FL) has emerged as a distributed collaborative AI approach that can enable many intelligent IoT applications, by allowing for AI training at distributed IoT devices without the need for data sharing. In this article, we provide a comprehensive survey of the emerging applications of FL in IoT networks, beginning from an introduction to the recent advances in FL and IoT to a discussion of their integration. Particularly, we explore and analyze the potential of FL for enabling a wide range of IoT services, including IoT data sharing, data offloading and caching, attack detection, localization, mobile crowdsensing, and IoT privacy and security. We then provide an extensive survey of the use of FL in various key IoT applications such as smart healthcare, smart transportation, Unmanned Aerial Vehicles (UAVs), smart cities, and smart industry. The important lessons learned from this review of the FL-IoT services and applications are also highlighted. We complete this survey by highlighting the current challenges and possible directions for future research in this booming area

Internet of things startups: state of the art and emerging trends

Internet of Things offers nowadays a range of solutions that can have a very relevant impact in many applications and industries. Over the last years, a lot of new companies have emerged with the purpose of not only gaining relevance in their markets but also pushing the boundaries of what IoT applications are capable of. For that reason, it made sense to conduct a research to understand what applications and industries have been the most interesting and had gathered more entrepreneurship in the last few years. This research aims at providing a deep understanding of the current context of the IoT startups, as well as analyzing what new emerging trends can be seen most recently that can help distinguish what the future of the IoT Market will look like. Three main areas are divided in this project: The first part is dedicated to understanding both the origins and the growth enablers that has caused IoT related applications to be so disruptive in the modern world. It is useful and necessary to set the base over which more precise and technical analysis can be build. Secondly, a quantitative analysis is performed in order to understand global trends in terms of funding and investments, applications, targeted market or type of offer. This scrutinization is key to understand the current state of the art and helps discern what are the main characteristics and trends to be further analyzed. Lastly, the same type of analysis is done following the emerging trends highlighted through the second phase of the project. In there, Smart Home, Smart Building and Smart Cities applications are examined to fully comprehend their relevance and paper inside the growth of the IoT Market.Outgoin

Low Cost Smart Automation System with Energy Meter

Automation and the Internet of Things (IoT) has become a hot topic in the present tech-driven world. Smart security solutions, smart home automation, smart health care, smart wearable’s etc. are in-trend applications of IoT, and by the near future we expect to see its application to a city's transportation system or smart power grids.. Nowadays there are lots of automation products that are available in the market but the cost of which is not affordable to the common man to use it at home or office. Home automation have various applications such as: Lighting control system, Appliance control and integration, Security, Leak and smoke detection, Home automation for the elderly and disabled etc[2]. Mostly all automation products needs special wiring and is not retro fit to their current switches. Automation for both smart and those who are not that smart should also be able to use automation. The research aims at finding sensors and IC’s that are cheap and with little modification on the software will reduce cost and making it small enough to fit into the current switch box so the little wiring will convert the current system to smart automatic system. It works on the principle of IOT with a central server to allow access from outside the premises of the system using mobile with internet connectivity. The energy meter also provides all the active and reactive power components of the equipment's connected to the system. In this project most of the objectives were achieved including features and cost optimization. Further research needs to incorporate camera and other security features