IP multicast receiver mobility support using PMIPv6 in a global satellite network

YesA new generation of satellite systems that support regenerative on-board processors (OBPs) and multiple spot beam technology have opened new and efficient possibilities of implementing IP multicast communication over satellites. These new features have widened the scope of satellite-based applications and also enable satellite operators to efficiently utilize their allocated bandwidth resources. This makes it possible to provide cost effective satellite network services. IP multicast is a network layer protocol designed for group communication to save bandwidth resources and reduce processing overhead on the source side. The inherent broadcast nature of satellites, their global coverage (air, land, and sea), and direct access to a large number of subscribers imply satellites have unrivalled advantages in supporting IP multicast applications. IP mobility support in general and IP mobile multicast support in particular on mobile satellite terminals like the ones mounted on long haul flights, maritime vessels, continental trains, etc., still remain big challenges that have received very little attention from the research community. This paper proposes how Proxy Mobile IPv6 (PMIPv6)-based IP multicast mobility support defined for terrestrial networks can be adopted and used to support IP mobile multicast in future satellite networks, taking cognizance of the trend in the evolution of satellite communications

IEEE Access Special Section Editorial: Big Data Technology and Applications in Intelligent Transportation

During the last few years, information technology and transportation industries, along with automotive manufacturers and academia, are focusing on leveraging intelligent transportation systems (ITS) to improve services related to driver experience, connected cars, Internet data plans for vehicles, traffic infrastructure, urban transportation systems, traffic collaborative management, road traffic accidents analysis, road traffic flow prediction, public transportation service plan, personal travel route plans, and the development of an effective ecosystem for vehicles, drivers, traffic controllers, city planners, and transportation applications. Moreover, the emerging technologies of the Internet of Things (IoT) and cloud computing have provided unprecedented opportunities for the development and realization of innovative intelligent transportation systems where sensors and mobile devices can gather information and cloud computing, allowing knowledge discovery, information sharing, and supported decision making. However, the development of such data-driven ITS requires the integration, processing, and analysis of plentiful information obtained from millions of vehicles, traffic infrastructures, smartphones, and other collaborative systems like weather stations and road safety and early warning systems. The huge amount of data generated by ITS devices is only of value if utilized in data analytics for decision-making such as accident prevention and detection, controlling road risks, reducing traffic carbon emissions, and other applications which bring big data analytics into the picture

Waste management in smart cities: Optimization of waste container’s capacity using fixed-frequency collection

One of the main problems of modern societies is the control of the production flow and removal of urban solid waste, due to the continuous massification of urban areas. This dissertation focuses on the need to reduce the impact of human activity over the environment through the management of urban solid waste. It describes how technological advancements can lead to an increase in the sustainability of urban development, through more efficient planning and reduction of logistics costs and pollution emissions. The work uses data of the product 360Waste from Evox Technologies, a company of a former student of ISCTE, operating in Castelo Branco. This company is specialized in creating an integrated solution for efficient collection of urban waste. This solution is composed of volumetric reading sensors, based on LoRaWAN technology. These sensors are installed in urban solid waste containers, which are always sending data to a LoRaWAN gateway, every time an individual opens the container. Based on the data collected from the sensors, the research work challenge will be to develop a solution to optimize the management of urban solid waste, by defining a uniform collection system and using technologies known as Data Sciences and Machine Learning.Um dos principais problemas das sociedades contemporâneas é o controlo do fluxo de produção e remoção dos resíduos sólidos urbanos, devido à massificação contínua das zonas urbanas. Esta dissertação incide sobre a necessidade de reduzir o impacto da atividade humana no meio ambiente, através da gestão dos resíduos sólidos urbanos. Neste trabalho é descrito como a evolução tecnológica pode conduzir a um desenvolvimento urbano mais sustentável, através de um planeamento mais eficiente, redução dos custos logísticos e das emissões poluentes. O trabalho utiliza dados de um produto 360Waste da Evox Technologies, uma empresa de um antigo aluno do ISCTE, que opera em Castelo Branco. Esta empresa é especializada na criação de uma solução integrada para a recolha eficiente de resíduos urbanos. Esta solução é composta por sensores de leitura volumétrica, com base na tecnologia LoRaWAN. Estes sensores são instalados em contentores de resíduos sólidos urbanos, que estão constantemente a enviar dados para uma Gateway LoRaWAN, cada vez que um indivíduo abre o contentor. Com base nos dados recolhidos dos sensores, o desafio deste trabalho de investigação será desenvolver uma solução para optimizar a gestão dos resíduos sólidos urbanos, definindo um sistema de recolha uniforme e utilizando tecnologias conhecidas como Data Sciences e Machine Learning

Dynamic Routing of Aircraft in the Presence of Adverse Weather Using a POMDP Framework

Each year weather-related airline delays result in hundreds of millions of dollars in additional fuel burn, maintenance, and lost revenue, not to mention passenger inconvenience. The current approaches for aircraft route planning in the presence of adverse weather still mainly rely on deterministic methods. In contrast, this work aims to deal with the problem using a Partially Observable Markov Decision Processes (POMDPs) framework, which allows for reasoning over uncertainty (including uncertainty in weather evolution over time) and results in solutions that are more robust to disruptions. The POMDP-based decision support system is demonstrated on several scenarios involving convective weather cells and is benchmarked against a deterministic planning system with functionality similar to those currently in use or under development