select a.companyid,a.companytitle,a.management_name,a.image,a.management_name2,a.magazine_id,a.image2,c.cat_id from companies a, vendor_select b, magazine_details c where a.companyid=b.vid and a.magazine_id=c.sno and b.catid = 0 and b.position!=0 and a.image2!='' and c.status != 0 and a.web_id = 27 and b.web_id = 27 and c.web_id = 27 order by b.position=0,b.position asc limit 4
The planning process of smart cities generates heaps of data containing valuable information, tables, and maps that are utilized in the construction projects.
FREMONT, CA: The emergence of new technologies such as artificial intelligence (AI), big data, and virtualization are transforming the approaches of processing information. However, the methods adopted in most cities are not only outdated but are also fraught with inefficiency. Hence, there is a need for the incorporation of modern technologies in the construction sector, such as Building Information Modelling, AI, and automation.
The planning process of smart cities generates troves of data, which often resides in the planning documents. It includes valuable information, tables, and maps utilized for the construction projects. The seemingly useless information may prove invaluable to the architects and developers. Before the construction, data, models, and digital maps are leveraged to assess the sites, proposals, and plans.
The cost of generating new data to bolster the plans is vast, as it is often stored in analog reports and planning applications. As a result, planning authorities have to finance new studies to obtain similar evidence. For instance, the datasets gathered during the evaluation of the housing market are identical to the data collected from community infrastructure levy, infrastructure capacity assessment, or a strategic housing availability evaluation. Since the datasets are managed manually, not only is the process slow and inaccurate, the interdependencies between the data are often buried.
The inefficiency in the process escalates when different city departments finance their data-driven strategies to evaluate public demands. The costs incurred from conducting various studies to collect similar data can be slashed significantly by analyzing past data and drawing useful conclusions. It will not only help in redirecting public funds to more useful processes but also streamline the planning approach.
There is a need for a centralized database to store the relevant data which can be accessed and utilized repeatedly across different departments. It will facilitate efficient upgrading of the information, at the same time, ensuring synergy between various planning commissions. Automating the process of updating the data will also eliminate the need for human intervention.
A centralized repository of relevant data will enable the local planning authorities to enhance data utilization during the planning process. It will not only streamline the development of local plans but will also help in making the process more transparent for the benefit of developers as well as citizens.