Sorting out trash and preserving old buildings
For 10 years, the subdistrict of Jing鈥檃nsi has consistently ranked top 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.
Altogether 98 percent of local families have registered for the subdistrict鈥檚 鈥済reen account鈥 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 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鈥檚 garbage station from 7-9am and 6-8pm. He advises residents on how to sort rubbish and is quite ready to pick out wrongly thrown waste and put it in the right litter bin.
Subdistrict officials have also installed sortable garbage bins in commercial areas. Activities are organized for white-collar workers, restaurant workers and cleaners so 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 analytic 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. In 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 asked to remove the bikes within half an hour.
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