Editing Affective computing (section)

=== Transportation ===
The applications of sensory computing may contribute to improving road safety. For example, a car can monitor the emotion of all occupants and engage in additional safety measures, such as alerting other vehicles if it detects the driver to be angry.<ref>{{cite web |date=30 August 2018 |title=In-Car Facial Recognition Detects Angry Drivers To Prevent Road Rage |url=https://gizmodo.com/in-car-facial-recognition-detects-angry-drivers-to-prev-1543709793 |website=Gizmodo}}</ref> In addition, affective computing systems for monitoring the driver's stress may allow various interventions such as driver assistance systems adjusted according to the stress level<ref>{{Cite journal |last1=Collet |first1=Christian |last2=Musicant |first2=Oren |date=2019-04-24 |title=Associating Vehicles Automation With Drivers Functional State Assessment Systems: A Challenge for Road Safety in the Future |journal=Frontiers in Human Neuroscience |volume=13 |page=131 |doi=10.3389/fnhum.2019.00131 |issn=1662-5161 |pmc=6503868 |pmid=31114489 |doi-access=free }}</ref> and minimal and direct interventions to change the emotional state of the driver.<ref>{{Cite book |last1=Balters |first1=Stephanie |last2=Bernstein |first2=Madeline |last3=Paredes |first3=Pablo E. |chapter=On-road Stress Analysis for In-car Interventions During the Commute |date=2019-05-02 |title=Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems |chapter-url=https://dl.acm.org/doi/10.1145/3290607.3312824 |language=en |publisher=ACM |pages=1–6 |doi=10.1145/3290607.3312824 |isbn=978-1-4503-5971-9|s2cid=144207824 }}</ref>