MCD likely to make budgetary allocation for monitoring of civic amenities through AI

The Municipal Corporation of Delhi is expected to make a budgetary allocation for the monitoring of civic amenities including solid waste management through Artificial Intelligence in its upcoming special budget meeting slated for December 8, according to an MCD source.

However, there is no official confirmation over this by the municipal.

The civic body is likely to set aside a significant amount of fund for the use of technology to deliver its daily services in three identified wards in the Shahdra South Zone, Karol Bagh Zone, and Central Zone, the source said.

According to the source, a blueprint of 100-day action plan based on the review and assessment of the Solid Waste Management (SWM) situation in these areas will be prepared to carry out the development work.

A third party agency is likely to prepare this action plan and audit the situation of SWM in the identified areas.

The works which could be executed with the use of Artificial Intelligence in the three MCD zones may include monitoring of roads, city infrastructure and creating support tickets for resolution.

A mobile phone application could be used to monitor the waste management in the identified areas for the ease of concerned officers at the Zonal level.

Earlier last month, the civic body had invited bids to clear 31,000 metric tonne of garbage lying alongside railway tracks setting a deadline to complete the work by April 2024 -- a part of MCD's Solid Waste Management Action Plan.

In absence of a standing committee, tenders for disposal of solid waste in the city remain in abeyance.

A tender of Rs 120 crore for disposal of solid waste in the central zone is stuck for approval as the standing committee is yet to be formed.

The last MCD House on November 29 witnessed major ruckus over delay in the formation of the standing committee with several opposition councillors demanding it be set up at the earliest.

(This story has not been edited by Devdiscourse staff and is auto-generated from a syndicated feed.)