Technologies Against Violence- Big Data & Applications in Use!

by Han-Ru Xie

In recent days, there have been violent incidents that no one had expected. In view of this, should science and technology be used to prevent such incidents, it is possible that we can live in a society with more comprehensive safety solutions against violence.

Emergency app to contact the police without making a sound

Since most citizens have little experience in dealing with emergencies, it is perhaps a good idea to turn to technology for self-protection , when it comes to conflicts with others or emergent situations. There are two emergency apps that may come in handy- 110 Video Call and 119+.

With 110 Video Call, an app developed by the National Police Agency, users only need to activate the APP, which will automatically pinpoint users’ location, start recording, and notify the police to head to where emergency services are needed. Users can also send out signals, without making a sound or speak, should they find themselves in danger.

119+, developed by the National Fire Agency, also automatically locates users and notify the police. An ambulance will immediately arrive head to the reported site, and it is also user-friendly to the hearing-impaired people, as they could report a case through texts.

Big data integrated and AI combined to prevent domestic violence

In cases where victims require protections, there have been means for risk assessment for social workers to determine the risk level of the reported case. However, the assessment is only an assistive measure, and the sound decisions can only be made with assessment plus analysis based on social workers experience in the field. That being said, social workers who do not have much practical experience are likely register all cases, for fear that applicants may fall victim to violence and abuse. This, in turn, may cause a waste of resources for administrative work


In 2017, Domestic Violence and Sexual Assault Prevention Center in Taipei City used data collected from different regions to compile reported data over the years, based on which a map is drafted to mark districts where domestic violence cases happen more often. In this way, authorities concerned can take the initiative in preventing such cases in each community. The Social Welfare Department under New Taipei City Government also puts forward a model for high-risk incident alert, targeted at cases on reported abuse on child and adolescents. Cases with similar details that are more often reported are identified, in order to prevent the recurrence of child abuse.

In the face of an aging society, the number of cases where elderlies are abused has increased. In 2019, the Department of Protection and Service under the Ministry of Health and Welfare proposed the AI Early Warning Analysis Pilot Program for Elderly Protection. A model for warning and case analysis using AI and machine leaning is built based on the case information stored in the database of a protection system. With this program, an early warning mechanism for possible incidents is built to assist the front-line social workers in protection of the elderly.

Conclusion

When it comes to violent incidents that cannot be prevented, should people be well-prepared in advance with the help of technology, they are more likely to stay calm in dealing with the situations, which, in turn, reduces possible harm.

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