Sorting out trash and preserving old buildings

For 10 years, the subdistrict of Jing'ansi has consistently ranked tops among Shanghai subdistricts and towns in terms of a beautiful, clean environment.

For 10 years, the subdistrict of Jing’ansi has consistently ranked tops among Shanghai subdistricts and towns in terms of a beautiful, clean environment.

According to subdistrict officials, the secret is to identify problems and then rectify them in a systematic, careful manner. That has been particularly true in efforts to preserve the local environment.

Some 98 percent of local families have registered for the subdistrict’s “green account” program, whereby participants accrue points for sorting their garbage into appropriate bins. The points can be redeemed for commodities such as milk and soap.

At neighborhood Lane 361 on Yuyuan Road, waste-sorting is practiced by every family. Senior residents like Luo Renjun have volunteered to help their neighbors to sort trash.

Every day, Luo is at the neighborhood’s garbage station from 7-9am and 6-8pm. He advises residents on how to sort rubbish and is quite to pick out wrongly thrown waste and put it in the right litter bin.

Subdistrict officials have also installed sortable garbage bins in commercial. Activities are organized for white-collar workers, restaurant workers and cleaners as to teach them proper trash sorting.

Besides many retail and office buildings, the subdistrict is also dotted with historical buildings. Officials are tapping into modern technology to preserve the old structures.

More than 600 sensors have been installed on historical buildings to detect vibrations and alert officials via a big data analytics platform. Officials then can check the buildings for illegal construction or other violations.

In addition, two drones fly over historical buildings as part of routine patrols. They can capture and record violations.

According to Hong Xuegang, deputy director of the subdistrict, the system solves problems created when historical buildings are still inhabited.

So far, the sensors have resulted in 35 alerts and 19 of them were deemed useful.

Another headache besetting almost every subdistrict is management of shared bikes.

The subdistrict has built a big data analysis platform to pinpoint the popular spots and peak hours for bike usage. That way, bikes can be dispatched to places they are needed during peak use hours.

Also, residents patrol the roads every day and report violations to officials. If bikes are found piled up or left idle, the operators of the shared programs are directed to remove the bikes away within half an hour.


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