# Sensors for Sustainable Smart Cities: A Review
## 3 Results
### Sensors
#### 3.3.2 Sensors for Mobility Applications  
Three main systems of urban mobility: vehicles, pedestrians, and traffic, are considered in this section. Due to the increasing number of vehicles every year in urban settlements, traffic jams, pollution, and road accidents tend to increase as well [56]. These problems suggest that there is an emergent need for intelligent mobility solutions. One such solution is intelligent traffic control, oriented to avoid traffic jams and optimize traffic flow [18]. Figure 4: (**a**) Epidermal electronic system (EES) made of a skin replica created from the forearm, before and; (**b**) after application of a spray-on-bandage; (**c**) Colourized microscopy image of the EES with conductive gold films of 100 \(\upmu\)m and; (**e**) its magnified view. (**d**) Microscopy image of EES with gold films of 10 \(\upmu\)m and; (**f**) its magnified view [48]. Due to repetitive starts and stops, fuel consumption and carbon emissions increase during traffic jams [18]. Therefore, providing solutions for traffic jams represents a direct positive impact in terms of urban mobility and air quality in cities. Moreover, heavy-duty vehicles (HDVs) and freight traffic release into the atmosphere large quantities of carbon emissions [57]. The automotive industry has put significant effort into developing more energy efficient powertrains (for example, hybrid electric vehicles). However, most HDVs are still fueled by diesel and providing optimal solutions to reduce the carbon emissions produced by these types of vehicles becomes a fundamental task [58]. Due to the COVID-19 pandemic, urban mobility underwent significant changes, such as a noticeable decrease in collective and individual transport, and with that a reduction in air pollution and carbon emissions [59]. This phenomenon has made governments and citizens consider future changes in post-lockdown mobility, to maintain cleaner environments in their cities. Applications in smart mobility include vehicle-vehicle (V2V), vehicle-infrastructure (V21), vehicle-pedestrian (V2P) [60], and vehicle-everything (V2X) connections (see Figure 5) [61]. Vehicles include several sensors needed for their proper operation, measuring several operational parameters of the vehicle, such as speed, energy consumption, atmospheric pressure, and ambient temperature [62; 63]. Such parameters are used to optimize speed profiles to minimize vehicle energy consumption considering traffic condition and geographical information. To achieve this aim, a cloud architecture is implemented that retrieves information from vehicle sensors and external services. In [64], an eco-route planner is proposed to determine and communicate to the drivers of heavy-duty vehicles (HDVs) the eco-route that guarantees the minimum fuel consumption by respecting the travel time established by the freight companies. Additionally, in this case, a cloud computing system is proposed that determines the optimal eco-route and speed and gear profiles by integrating predictive traffic data, road topology, and weather conditions. Vehicle weight and speed regulation are also important to ensure road and passengers safety, helping in the avoidance of serious accidents [65]. Efforts in increasing pedestrian's safety are valuable contributions in improving urban mobility [66]. Regarding traffic, conventional traffic light systems are defined in a non-flexible structure, such that light transitions have defined delays and onsets [67]. Dynamic changes in traffic volume, congestions, accidents, and pedestrian confluence, should have been considered to provide an optimized traffic control [67]. Pedestrian's movement and behavior in urban settings have been monitored mainly using cell phones, by monitoring call detail records (CDRs) [68], social media check-ins [37; 69], MAC address reading [70], and smart cards detection in public transport [71].