IoT Platforms and Technologies Driving Spatial Planning and Analytics

Introduction

In 2015 all 196 participant states of the international conference on climate changes (COP21) agreed in the urgency of reducing greenhouse gas emissions to avoid the rise of 2°C of the mean atmosphere temperature with respect to pre industrial era United Nations (2015). Recently, the Intergovernmental Panel on Climate Change (IPCC) have analysed the difference between an increase of 2° and an increase of 1.5° Masson-Delmotte et al. (2018). The report states that keeping the increase of temperature below 1.5° with respect to the pre-industrial era will mitigate the catastrophic impacts of climate change. To achieve this goal IPPC states that we must reduce the level of CO₂ emission by 2030 of at least of 45% with respect to the levels in 2010 and have net zero emissions for 2050. Furthermore, the report states that “pathways limiting global warming to 1.5°C with no or limited overshoot would require rapid and far-reaching transitions in energy, land, urban and infrastructure (including transport and buildings), and industrial systems.” Urbanizations are largely energy-intensive as reported by the UN habitat division, cities consume about 75% of the global primary energy supply and are responsible for about 50-60% of the world’s total greenhouse gases United Nations (2017). Moreover, the majority of the consumed energy is still supplied by fossil fuels (coal, oil and gas). In 2016, more than half of the overall world’s population is living in urban areas. Projections states that by 2030, urban areas will host around 60% of people globally and one third of the population will live in cities with at least half a million inhabitants United Nations (2016). The International Energy Agency (IEA) states that buildings represent 40% of total final energy consumption in most countries. Heating and cooling systems in buildings consume the 60% of energy in the residential sector and 45% in the service sector IEA (2014). On this regard, in the last years, many countries are providing incentives to promote the deployment of low-carbon and sustainable energy production technologies (Dusonchet & Telaretti, 2010), generation such as Photovoltaic (PV) Systems. In order to achieve a reduction of greenhouse gas emission an increasing installation of Renewable Energy Sources (RES), Distributed Generation (DG) and an optimization of consumption with a smart use of energy in our cities are required

IEA (2016). ICT technologies, in particular Internet of Things (IoT), allows to control and optimize energy consumption Wigle (2014), hence increasing energy efficiency. In the last years, we have assisted to the spread deployment of IoT devices in our lives and cities. Such devices allow to monitor and interact with objects through the Internet. Furthermore, a massive deployment of IoT devices in our city is constantly increasing the amount of collected data that needs to be stored and analysed. Big data techniques can help in managing and such huge amount of information. In this context, we need distributed software platforms that can enable the concentricity and interoperability of such heterogeneous devices. Furthermore, such platforms will integrate Big Data technologies to deal with the volume and frequency of data generated by the IoT devices.