A Systematic Evaluation of Literature on Internet of Things (IoT) and Smart Technologies with Multiple Dimensions

The advent of state of the art advanced technologies is necessitated by the ever-increasing onset and infiltration of our lives by the smart devices and gadgets for providing an array of services. The conventional methods and techniques already becoming obsolete and the consistent and persistent demand for provision of high end services with a greater degree of accuracy by various sectors, paves the way for collaboration of smart technologies such as Internet of things, Internet of everything, Internet of Vehicles etc. with the smart gadgets and devices. This systematic review tries to explore the avenues for research and multiple streaming of segments by the analysis of allied smart systems comprising of smart devices and multi-dimensional IoT, IoE, IoV etc.&nbsp

Gestión de la seguridad vial y contratos por niveles de servicio en el corredor vial Pro Región Puno, 2021

La presente investigación tuvo por objetivo, determinar la gestión de la seguridad vial y contratos por niveles de servicio en el corredor vial Pro Región Puno, 2021, la investigación fue cuantitativa, descriptiva, no experimental de diseño correlacional. La población estuvo compuesta los operadores de transporte comunales y urbanos de la región, tomando una muestra probabilística de 46 operadores. Como instrumentos se utilizó el Cuestionario de Gestión de la seguridad vial y el Cuestionario de gestión de contratos por niveles de servicio. Los resultados nos permiten concluir: Sobre el objetivo general, se logró demostrar que existe relación entre la gestión de la seguridad vial y los contratos por niveles de servicio en el corredor vial Pro Región Puno, 2021, se logró demostrar que existe relación y esta es de intensidad alta (Rho = 0.814, p= 0.000, alfa = 0.05); Sobre el objetivo específico 1, se logró determinar relación entre la dimensión determinación de riesgos viales y la variable contratos por nivel de servicio en el corredor vial Pro Región Puno, 2021, y esta fue de intensidad media (Rho = 0.606, p= 0.000, alfa = 0.05); Sobre el objetivo específico 2, se logró determinar relación entre la dimensión planeación de prevención de riesgos y la variable contratos por nivel de servicio en el corredor vial Pro Región Puno, 2021, y esta es de intensidad alta (Rho = 0.775, p= 0.000, alfa = 0.05); Sobre el objetivo específico 3, se logró determinar relación entre la dimensión requerimientos de inclusión de prevención de riesgos la variable contratos por nivel de servicio en el corredor vial Pro Región Puno, 2021, y esta fue de intensidad alta (Rho = 819, p= 0.000, alfa = 0.05)

Computer Vision and Internet of Things Application to Enhance Pedestrian Safety

With the increasing population, the issue of pedestrian safety is currently of major concern in most cities of the world. Pedestrian safety is concerned with ensuring the well-being of pedestrians and reducing the potential risk areas as well as implementing measures to reduce accidents. The aim of this study is to propose a computer vision and cloud-based solution that enhances pedestrian safety by collecting, visualizing and analyzing pedestrian and vehicular data across different intersections in the city of Montreal. In the past, the rate of accidents in the City of Montreal involving pedestrians has been quite high, therefore a method to solve this problem has led to this study. About 200,000 images were collected across 43 intersections in the city of Montreal from the Traffic cameras – Ville de Montreal website. The data was collected from March 8, 2020, up until March 22, 2020 and then from May 1st, 2020 to 11th May 2020. An object detection and classification model using Faster RCNN algorithm to identify pedestrian and vehicles at the intersection was implemented. Further, this model was used to obtain a dataset showing the number of pedestrians and vehicles at the intersections. The information obtained from this data set was used for visualization and in-depth analysis of the pedestrian and vehicle data in order to derive patterns of peak and non-peak hours and high-risk intersections. IV Furthermore, zero inflation poisson distribution model was implemented on our dataset to display the timings and intersections which had zero pedestrian counts for long hours of the day as compared to the vehicle count. A heat map was generated to visualize the dataset and to assist data viewers to identify which areas should get most attention. Finally, we created a prototype solution that mimicked the traffic control system by utilizing LEDs and microcontrollers (IoT device), cloud services, publish/subscribe model, and object detection. To implement this prototype, the data obtained through the object detection model was sent onto the cloud (Cloud MQTT), from where it was used to control the programmed microcontrollers (IoT devices) present at the different intersections based on the vehicle and pedestrian counts. The system managed to show excellent accuracy for detection of vehicles and pedestrians on the dataset, and the delay experienced in controlling the microcontroller was also negligible, thus making our system effective and reliable

An IoT Architecture for Assessing Road Safety in Smart Cities

The Safe System (SS) approach to road safety emphasizes safety-by-design through ensuring safe vehicles, road networks, and road users. With a strong motivation from the World Health Organization (WHO), this approach is increasingly adopted worldwide. Considerations in SS, however, are made for the medium-to-long term. Our interest in this work is to complement the approach with a short-to-medium term dynamic assessment of road safety. Toward this end, we introduce a novel, cost-effective Internet of Things (IoT) architecture that facilitates the realization of a robust and dynamic computational core in assessing the safety of a road network and its elements. In doing so, we introduce a new, meaningful, and scalable metric for assessing road safety. We also showcase the use of machine learning in the design of the metric computation core through a novel application of Hidden Markov Models (HMMs). Finally, the impact of the proposed architecture is demonstrated through an application to safety-based route planning