Integrating air quality into urban navigation

A non-transitory computer readable medium, non-transitorily storing first computer instructions which, when executed by at least one processor instantiates an enviro-engine which configures a user device to route a user from a current location to a destination by performing routing operations comprising:

• determining, by the user device, a current user location (“CUL”) of a user;
• receiving, by the user device, for the CUL first digital mapping data identifying a current user location air quality environment (“CULAQE”);
• wherein a geographic area corresponding to the CULAQE varies over time with weather changes;
• determining, by the user device, while the user device is located within the CULAQE, and based on air quality data received from at least one Internet-of-Things (“IoT”) sensor within direct wireless range of the user device, a current user location air quality index (“CULAQI”);
• determining, by the user device, a destination location (“DL”) for a destination;
• determining, by the user device, a plurality of route segments (“RS”), including a current route segment (“CRS”) and a plurality of transient route segment (“TRS(n)”), from the CUL to the DL;
• determining, by the user device, a first optimization of the plurality of route segments based on the CULAQI and a destination location first air quality index (“DLAQI(1)”);
• determining, for the TRS (n), based on air quality data received from an IoT sensor located within a transient air quality environment (“TAQE”) for each of the TRS(n) and while the IoT sensor is within direct wireless range of the user device, a plurality of transient air quality indexes (“TAQI(s)”) including a first transient air quality index (“TAQI(1)”) and a plurality of additional air quality indexes (“TAQI(n)”);
• determining, by the user device and while the user device travels across the TRS(n) to the DL, a plurality of second optimizations of the TRS(n) based on the DLAQI(1), a plurality of additional destination location air quality indexes (“DLAQI(n)”), the TAQI(1), and the plurality of TAQI(n);
• and
• continually re-determining the plurality of second optimizations while the user device travels from the CUL to the DL.

A user device comprising:

• a processor;
• a non-transitory data store storing non-transitory computer instructions;
• and
• a network interface;
• wherein the processor, when executing the non-transitory computer instructions instantiates an enviro-engine which configures the user device to route a user from a current location to a destination by performing routing operations comprising:
• determining a current user location (“CUL”) of a user;
• obtaining, for the CUL, a current user location air quality environment (“CULAQE”);
• wherein a geographic area corresponding to the CULAQE varies over time with weather changes;
• determining, for the CULAQE, a current user location air quality index (“CULAQI”);
• wherein the CULAQI is determined based on air quality data received from an Internet-of-Things (“IoT”) sensor located within the CULAQE and within direct wireless range of the user device;
• determining a destination location (“DL”) for a destination;
• determining a plurality of route segments (“RS”), including a current route segment (“CRS”) and a transient route segment (“TRS”) from the CUL to the DL;
• performing a first optimization of the CRS based on the CULAQI;
• obtaining, for the DL, a destination location air quality environment (“DLAQE”);
• obtaining, for the DLAQE, a plurality of destination location air quality indexes (“DLAQI(s)”) including a first destination location air quality index (“DLAQI(1)”) and a plurality of additional destination location air quality indexes (“DLAQI (n)”);
• wherein the DLAQI is determined based upon at least one past condition for the DLAQE;
• receiving first real-time air quality index data (“RAQI”) for the DLAQE;
• performing a second optimization of the CRS based on the RAQI for the DLAQI(s);
• identifying a plurality of transient air quality environments (“TAQE(s)”) including a first transient air quality environment (“TAQE(1)”) and at least one additional transient air quality environment (“TAQE(n)”);
• obtaining, over time and for the TAQE(s), a plurality of transient air quality indexes (“TAQI(s)”) including a first transient air quality index (“TAQI(1)” and at least one additional transient air quality index (“TAQI(n)”);
• wherein the TAQI(s) are determined based on air quality data received from an IoT sensor located within the TAQE(s) and within direct wireless range of the user device at a given time while the user device travels from the CUL to the DL;
• performing a third optimization of at least one of the CRS and the TRS (n) based on the TAQI(s);
• receiving a second RAQI for the DLAQE;
• and
• performing a fourth optimization of at least one of TRS (n) based on the second RAQI.