Timely and reliable packets delivery over Internet of Vehicles (IoVs) for road accidents prevention: a cross-layer approach

With the envisioned era of Internet of Things (IoTs), all aspects of Intelligent Transportation Systems (ITS) will be connected to improve transport safety, relieve traffic congestion, reduce air pollution, enhance the comfort of transportation and significantly reduce road accidents. In IoVs, regular exchange of current position, direction, velocity, etc., enables mobile vehicles to predict an upcoming accident and alert the human drivers in time or proactively take precautionary actions to avoid the accident. The actualization of this concept requires the use of channel access protocols that can guarantee reliable and timely broadcast of safety messages. This paper investigates the application of network coding concept to increase content of every transmission and achieve improved broadcast reliability with less number of retransmission. In particular, we proposed Code Aided Retransmission-based Error Recovery (CARER) scheme, introduced an RTB/CTB handshake to overcome hidden node problem and reduce packets collision rate. In order to avoid broadcast storm problem associated with the use of RTB/CTB packet in a broadcast transmission, we developed a rebroadcasting metric used to successfully select a vehicle to rebroadcast the encoded message. The performance of CARER protocol is clearly shown with detailed theoretical analysis and further validated with simulation experiments

An Application Of Machine Learning With Boruta Feature Selection To Improve NO2 Pollution Prediction

Projecting and monitoring NO2 pollutants' concentration is perhaps an efficient and effective technique to lower people's exposure, reducing the negative impact caused by this harmful atmospheric substance. Many studies have been proposed to predict NO2 Machine learning (ML) algorithm using a diverse set of data, making the efficiency of such a model dependent on the data/feature used. This research installed and used data from 14 Internet of thing (IoT) emission sensors, combined with weather data from the UK meteorology department and traffic data from the department for transport for the corresponding time and location where the pollution sensors exist. This paper select relevant features from the united data/feature set using Boruta Algorithm. Six out of the many features were identified as valuable features in the NO2 ML model development. The identified features are Ambient humidity, Ambient pressure, Ambient temperature, Days of the week, two-wheeled vehicles(counts), cars/taxis(counts). These six features were used to develop different ML models compared with the same ML model developed using all united data/features. For most ML models implemented, there was a performance improvement when developed using the features selected with Boruta Algorithm

Benefits and Challenges of Internet of Things for Telecommunication Networks

Recently, Internet of things (IoTs) has become the main issue in designing monitoring systems such as smart environments, smart cars, and smart wearable devices. IoTs has transformed the life of people to be more adaptable and intelligent. For example, in a healthcare monitoring system, using smart devices will improve the performance of doctors, nurses, patients, and the healthcare industry. The IoTs revolution is known as the fourth industrial revolution and would change the way humans interact with machines and lead the way to a high-technology machine-to-machine interaction. In fact, almost every device around us would be connected to Internet, collecting and exchanging data with other devices on the cloud. In this chapter, we will introduce the benefits of IoTs on telecommunication networks and its challenges to give a complete overview for researchers to know how to improve our life and society by building smart IoTs systems

Cognitive radio-enabled Internet of Vehicles (IoVs): a cooperative spectrum sensing and allocation for vehicular communication

Internet of Things (IoTs) era is expected to empower all aspects of Intelligent Transportation System (ITS) to improve transport safety and reduce road accidents. US Federal Communication Commission (FCC) officially allocated 75MHz spectrum in the 5.9GHz band to support vehicular communication which many studies have found insufficient. In this paper, we studied the application of Cognitive Radio (CR) technology to IoVs in order to increase the spectrum resource opportunities available for vehicular communication, especially when the officially allocated 75MHz spectrum in 5.9GHz band is not enough due to high demands as a result of increasing number of connected vehicles as already foreseen in the near era of IoTs. We proposed a novel CR Assisted Vehicular NETwork (CRAVNET) framework which empowers CR enabled vehicles to make opportunistic usage of licensed spectrum bands on the highways. We also developed a novel co-operative three-state spectrum sensing and allocation model which makes CR vehicular secondary units (SUs) aware of additional spectrum resources opportunities on their current and future positions and applies optimal sensing node allocation algorithm to guarantee timely acquisition of the available channels within a limited sensing time. The results of the theoretical analyses and simulation experiments have demonstrated that the proposed model can significantly improve the performance of a cooperative spectrum sensing and provide vehicles with additional spectrum opportunities without harmful interference against the Primary Users (PUs) activities

Prototipo para el monitoreo de la contaminación acústica, como herramienta para el empoderamiento de la sociedad

Objective: Acceptable levels are between 45 and 65 dB according to the OMS, exceeding these values ​​can affect mental and physiological health, deteriorating the quality of life of the inhabitants. The purpose of this research is to identify the levels of noise pollution in the historic center of the city of Popayán, Cauca, Colombia, during peak hours of midday.Method: Applying the Design Thinking methodology, a prototype based on the Internet of Things (IoT) and a mobile application were designed to monitor the acoustic level in real time, and thus offer a technological tool that contributes to the empowerment of society in relation to its environmental conditionsResults:  Results: The software solution was developed for Android mobile devices, in operating system versions higher than 6.0 (Marshmallow), using tools such as Android Studio and Firebase. As a perspective of this work, it is suggested to make measurements for longer periods of time, and in several places in the city.                                                                                       Conclusions: Real-time measurements of the level of noise pollution, for example, through the application and measurements made during 9:11 A.M. and 6:31 p.m., on February 11, 2022, it was possible to deduce that the average level of noise pollution was 61.48 dB and that, in the measurements made in the morning, they were the ones with the highest levels of pollution. , being the data of 11:01 A.M.Objetivo: Los niveles aceptables están entre 45 y 65 dB según la OMS, al superar estos valores se puede afectar la salud mental y fisiológica, deteriorando la calidad de vida de los habitantes. El objeto de esta investigación es identificar los niveles de contaminación acústica en el centro histórico de la ciudad de Popayán, Cauca, Colombia, en horas pico del mediodíaMetodología: Aplicando la metodología Design Thinking se diseñó un prototipo basado en Internet de las Cosas (IoT) y una aplicación móvil que permite monitorear el nivel acústico en tiempo real, y así, ofrecer una herramienta tecnológica que contribuya al empoderamiento de la sociedad en relación a sus condiciones ambientales Resultados: La solución software fue desarrollada para dispositivos móviles Android, en versiones de sistema operativo superiores a la 6.0 (Marshmallow), utilizando herramientas como Android Studio y Firebase. Como perspectiva de este trabajo, se sugiere hacer mediciones por periodos de tiempo más prolongados, y en varios sitios de la ciudad. Conclusiones: las mediciones en tiempo real del nivel de contaminación acústica, por ejemplo, por medio de la aplicación y las mediciones realizadas durante las 9:11 A.M.  y las 6.31 P.M., del día 11 de febrero de 2022, se pudo deducir que el promedio del nivel de contaminación acústica fue de 61.48 dB y que, en las mediciones realizadas en horas de la mañana, fueron las que tuvieron niveles más altos de contaminación, siendo el dato de las 11:01 A.

The Right to the Sustainable Smart City

Environmental concerns have driven an interest in sustainable smart cities, through the monitoring and optimisation of networked infrastructures. At the same time, there are concerns about who these interventions and services are for, and who benefits. HCI researchers and designers interested in civic life have started to call for the democratisation of urban space through resistance and political action to challenge state and corporate claims. This paper contributes to an emerging body of work that seeks to involve citizens in the design of sustainable smart cities, particularly in the context of marginalised and culturally diverse urban communities. We present a study involving co- designing Internet of Things with urban agricultural communities and discuss three ways in which design can participate in the right to the sustainable smart city through designing for the commons, care, and biocultural diversity

Are smart innovation ecosystems really seeking to meet citizens’ needs? Insights from the stakeholders’ vision on smart city strategy implementation

The concept of a smart city is becoming the leading paradigm worldwide. Consequently, a creative mix of emerging technologies and open innovation is gradually becoming the defining element of smart city evolution, changing the ways in which city administrators are organizing their services and development globally. Thus, the smart city concept is becoming extremely relevant on the agendas of policy-makers as a development strategy for enhancing the quality of life of the citizen and improving the sustainability goals of their cities. Despite of the relevance of the topic, still few studies investigate how open innovation shapes the way cities become smarter or focus on the experiences of professionals to understand the concept of a smart city and its implementation. This paper fills this gap and analyzes the processes for building effective smart cities by integrating the different perspectives of smart innovations and using the core components of smart cities according to a conceptual framework developed in previous research. In so doing, it provides useful insights for smart city stakeholders in adopting social and technological innovation to improve the global competitiveness of their cities. The empirical dataset allows examining how “smart cities” are being implemented in Manchester (UK), and in Boston, Massachusetts, and San Diego City (United States of America (USA)), including archival data and in-depth interviews with core smart city stakeholders who are involved in smart city projects and programs across the cases. Results from empirical data suggest that the conceptualization of smart cities across the cases is similar with a strong emphasis on social and technological innovation aimed at addressing municipal challenges in the core sub-systems of the cities, which include mobility, environmental sustainability, entrepreneurial development, quality of life, and social cohesion. The results also reveal benefits and challenges relating to smart innovation ecosystems across the cases and the future directions of their diffusion