Heat waves are a leading cause of weather related fatalities world-wide. Due to increasing urbanisation, climate change and an ageing population, health risks for urban populations will continue to increase in the coming years. The effect of urban heat islands on the health of vulnerable groups where especially the elderly population is hit the hardest, is widely recognized in literature. In past studies the effect of heat has been modelled for the entire population of a city or state where outside temperature measures or land surface temperature is the hazard. Research on specific vulnerable groups such as the elderly is relatively sparse to this date. In this study various datasets have been combined with the aim of providing a method for the development of a heat-related elderly risk index (HERI) for the elderly population of The Hague. The final composite risk indexes have been constructed for three moments in the day on the 27th of July which was the hottest day of the heat wave of 2018. The structure of the index is based on Crichton’s Triangle of Risk, which states that risk is a function of hazard, exposure, and vulnerability. By selecting the following indicators to represent the spatial layers: physiological equivalent temperature, indoor temperature, facade orientation, being 75 years or older, loneliness among people over the age of 75, and population density. The indicators are assigned a weight trough the Analytical Hierarchy Process (AHP), after which the indicators can be combined into a HERI maps for the three timestamps. Different configurations of indicators have been used for creating the HERI maps, yielding different weights for each set. This resulted in two types of HERI maps: HERI-2 and HERI- 3. HERI-2 exists of physiological equivalent temperature, being 75 years or older, loneliness among people over the age of 75, and population density. HERI-3 is composed of the same indicators as HERI-2 but instead of physiological equivalent temperature, indoor temperature is used as the hazard. The HERI maps for the three timestamps have been validated by performing a Pearson Correlation between the HERI maps and the mortality numbers among the elderly in the days after the heat wave. The indicators and mortality are non correlated except for the indicator ’being 75 years or older’. However when the indicators are combined into the HERI index maps a weak positive correlation with mortality can be seen. The results indicate that it is necessary that the indicators have to be re-evaluated and several weighting methods have to be considered in order to improve the HERI.

This synthesis project is focused on implementing an Internet of Things (IoT) network to measure environmental data in the city of Delft. This network consists of sensor platforms that are placed in the urban environment. Each sensor platform is mounted on fixed locations and it is not moved during the measurement time. The aim is to raise community’s environmental awareness to improve the quality of the environment.
Recent developments in technology made it possible to fabricate small, efficient, and reliable sensors boards which are the base of these sensors platforms and making them efficient and reliable. Sensor boards like Arduino, Raspberry Pi, and LoPy are some examples of these small sensor boards. In this project, the LoPy is used which is a sensor board that is equipped with Bluetooth Low Energy, Wifi and a LoRa radio. This last one is a communication technology that makes longer communication distances possible.
The sensor network measures four different environmental indicators that will be distributed to the public: temperature, humidity, noise and air quality. The network then communicates via LoRa this data to one centralized server where the data is stored, processed and sent back to the citizens. This data is made publicly accessible to academia, citizens and the stakeholders alike. The network is also made interactive, people who pass by can interact with the sensors and request specific environmental data in real time.
The sensor network has been build and deployed in the city. During the uptime of the network it succeeded to provide the data to the citizens via the feedback mechanisms: a website with a dashboard and an automated twitter account. Local differences have been measured with temperature and humidity sensors. With regard to the noise sensor and air quality sensors no definitive conclusions could be drawn.