Participatory Urban Planning Through Gig Workers Integration
**Pawni Singh and Prikshit Rathore
India’s gig economy workers are “real-time data capturers” endowed with distinctive ground-level spatial intelligence. Their field insights and power to sense the city are not capitalised on by city planners and policymakers. This piece advocates for the incorporation of gig workers’ data by utilising digital public infrastructures that have the possibility to eliminate the mobility divide. It advocates for a system of rewards to promote the inclusive participatory engagement of the gig workforce in the development of smart, data-driven, inclusive urban areas.
Introduction
Who truly understands the city? Beyond the blueprints of planners, it is the Gig workers navigating its pulse daily. Gig workers have the in-depth knowledge and the ability to sense the city as their work demands it. This special insight puts them in the position of a “real-time data capturer”: they know where to look for flooded lanes or where street lights or drinking water taps are most needed. Those whose presence is felt throughout the city or who know the city’s nerve system hardly ever get consulted by planners. This article addresses the issue of underutilised knowledge sources by arguing that bypassing the knowledge and experiences of gig workers cannot be ignored; their spatial movement data and observations constitute a mobility divide that has the potential to enhance urban efficiency. The article asserts that planners must develop formal channels to harvest these key insights (e.g., app-based data sharing, rider surveys, and participatory councils). The integration of gig workers as active stakeholders is a means of achieving inclusive urban development.
The Urban Footprint of India’s Gig Workforce: Scale and Significance
In 2020-21, there were approximately 77 lakh platform-based workers. Leading platform operators include Zomato and Swiggy (food delivery), Ola and Rapido (ride-hailing), among others. According to one study, India’s gig workforce is going to grow to about 23.5 million by 2029-30. It is estimated that the gig economy’s market size will reach $1,847 billion worldwide by 2032. These estimated numbers are crucial for participatory urban planning, providing a new way for urban planners to incorporate their valuable inputs and experiences. At the same time, gig workers generate value, which is inseparable; it stems from the techno-economic structure of their urban navigation. Unlike other informal sectors, such as street vendors, domestic workers or waste pickers, gig workers’ engagement unfolds between economic incentives and spatial behaviour playing out across three critical dimensions: one, 24/7 omnidirectional spatial oversight; largely, informal workers operate fixed daytime routes between home and work. Their presence during late-night and early-morning hours constitutes a de facto nighttime audit, surfacing infrastructure issues that are unseen to standard daytime municipal audits. From an economic angle, they function as a pre-existing, privately funded sensor network that the state can utilise without investing in the large capital outlay otherwise required for 24/7 physical monitoring. Two, economic reliability and automated verification; unlike domestic or construction workers, whose spatial understanding is largely anecdotal and experiential, gig labour occurs inside a framework of automated proof of presence. Their observations are ingrained in economic activity; a delay caused by waterlogging or a pothole is equivalent to safety concerns, lost incentives, and lower ratings. This arrangement creates a natural verification mechanism: because their income depends on efficiently navigating infrastructure, their data has an operational reliability that subjective complaints lack. When a delivery rider’s movement slows at a given coordinate due to poor infrastructure, it constitutes a digitally verified service event with GPS traces and timestamps, a byproduct of regular work. Three, interoperability with existing digital public infrastructure(DPI): gig work is technically compatible with India’s existing DPI, as it is already mediated through platform-based digital architecture.
This compatibility is the critical technical distinction. Repurposing the e-Shram ID as a verified digital credential and the Integrated Command and Control Centres (ICCCs) as data clearinghouses creates an institutional handshake that remains technically feasible for the informal sectors lacking digital mediation. These initiatives have broader implications for policy formulation and implementation, within the larger discussion of participatory and inclusive development. However, the contribution of informal workers cannot be bypassed directly, but the challenge lies in their functioning and reach. Most of the informal workers do not use the platform, and they have very limited reach or are restricted to a particular area or locality. To incorporate inputs for policy formulation, a larger dataset and reach are required, and data may be generated digitally.
The Digital Handshake: Embedding Real-Time Mobility Data in Urban Planning
The major challenge for the administration lies in where to house this data. The solution lies in utilising India’s current DPI rather than creating new platforms from scratch to serve as a channel for gig worker’s insight. The most pragmatic approach is to utilise the e-Shram portal, which currently houses data on nearly 289 million unorganised workers of India. Currently, it’s a welfare registry, but it possesses the capacity to transform into a two-way engagement platform. By integrating gig-job-specific sections, the Ministry of Labour could provide customised surveys in vernacular languages to workers in mapped pin codes. The following elevates the e-Shram ID from just a registration number to a digital credential for administration and auditing, enabling them to assess infrastructure quality by using the most extensive workforce.
At the municipal level, these national datasets can be augmented through the ICCCs established under the Smart Cities Mission (SCM). These centres are designed to handle real-time data. However, SCM lacks public participation, relies heavily on consultants, and lacks a basic dataset of amenities. The learning from SCM suggests that only the integration of technology into cities’ services alone cannot solve problems when planning and decision-making are imposed in an ad hoc, top-down manner. It means technology has not failed, but there is a need to rethink the planning mechanism and the decision-making process. It is the right time when technology integration becomes a need of the hour; Indian cities can incorporate aggregated feeds from startups straight into ICCCs dashboards when they seek to open Application Programming Interfaces [APIs]( A software interface that allows different digital platforms to communicate and exchange data securely) for non-personal mobility data. This connection will help traffic controllers spot areas with heavy traffic by analysing the real-time slowdowns of many gig workers, offering a level of data insight that fixed cameras can’t provide. Further challenge pertains to how such data will be collected, ensuring that it respects the worker’s digital rights and time. The most feasible approach embeds feedback mechanisms directly within workers’ platform interfaces, rather than requiring workers to complete separate surveys or attend external workshops via a one-tap reporting mechanism. Building upon existing civic reporting models, notably India’s Swachhata App, following such models, an embedded API could facilitate low-burden reporting during workers’ existing downtime. Rather than imposing additional labour, this approach leverages the brief waiting periods (between passenger pickups or between deliveries) to capture infrastructure issues through geotagged photos of a waterlogged service lane, a pothole, or a broken streetlight. To ensure precision in India’s dense urban clusters, this system should include the Department of Posts ‘DigiPin’ (Digital Postal Index Number). This integration would enable workers to tag the pinpoint geospatial locations with high precision.
However, a critical gap often exists between data collection and planning action. The technological infrastructure alone remains insufficient; effectiveness depends on administrative mechanisms that translate collected data into actionable plans. A suitable model in the Indian context is the Town Vending Committee (TVC), established under the Street Vendors (Protection of Livelihood and Regulation of Street Vending) Act, 2014. An analogous reform involves establishing City Logistics Committees in every municipality. These bodies would bring together traffic police, municipal engineers, platform policy heads, the gig worker union, and urban city planners to review the mobility data quarterly. This institutional framework will ensure that the data gathered leads to tangible policy outcomes.
The efficacy of these participatory models is further demonstrated by comparative worldwide experience. Data from global cities indicates that including gig workers in city planning is both viable and capable of producing tangible infrastructure enhancements. In Singapore, the Urban Redevelopment Authority formalised worker involvement via a tripartite Last-Mile Deliveries Workgroup, which systematically integrated delivery rider’s mobility data and experience comments into urban design decisions. This procedure resulted in targeted redesigns of high-traffic commercial centres. At i12 Katong, automobile lanes were transformed into exclusive rider bays with specified parking and waiting areas, informed by rider traffic analyses. These measures demonstrate how data gathered from workers’ spatial knowledge can lead to meaningful and practical infrastructure improvements. While Singapore’s governance model is an aesthetic vision for Indian cities that may provide direction for urban planning and solutions to modern urban issues, this imaginative thinking serves as a vital way to choose a path for the future by breaking conventional barriers. However, such a model cannot be replicated directly in any Indian program due to differences in scale and institutional structure; without these local adaptations, the approach remains merely old wine in a new bottle.
Nevertheless, participation is conditioned upon an unambiguous and well-established equilibrium between civic duty and one’s means of living. The administration should develop a robust incentive model that enables gig workers to receive payment for tasks beyond data collection and other forms of work. Using “Welfare-Linked Gamification,” verified reports of hazards will be rewarded with “Civic Contribution Points” that will be displayed in their e-Shram profile. These points will function as a digital currency to receive certain benefits, such as subsidised Pradhan Mantri Suraksha Bima Yojana premiums or quicker PM SVANidhi micro-loan processing. By treating reporting as an economic asset, the state protects the data stream and, in turn, enhances the financial resilience.
The integration of various digital platforms for better planning has become an urgent need for cities’ institutions. However, the functioning of Indian cities through municipal corporations and parastatal agencies makes integration a tedious task for the planning mechanism. With the incorporation of technology, many cities such as Ahmedabad, Aizawl, Diu, Gandhinagar and more serve as examples of digital integration. In the age of technology, sharing platforms are not a new development; they are a standard practice in an advanced technological state, as many online marketing and shopping platforms have done. We know the challenges of digital integration, as Indian cities are a complex entanglement of various configurations that need to be integrated to improve functioning and development.
Conclusion
Urban infrastructure has been the subject of detailed, real-time mapping, as seen in the case of India’s 7.7 million gig workers, who are often overlooked through surveys and satellite imagery. This spatial intelligence is usually excluded from city planning, either stored in proprietary databases or dismissed as complaints. This oversight is an opportunity for inclusive urban development that has been missed. Changing the current scenario includes four steps: First, policymakers should recognise the gig workers as actual “real-time data capturers” of the city. Second, developing mechanisms to extract knowledge using existing tools, such as the e-Shram portal, ICCC, and City Logistics Committees. Third, ensure that this data is considered and utilised on rather than being pushed to archives. Fourth, the workers should be financially incentivised to invest their time in sharing this valuable data with the administration.
**Pawni Singh is a III-year B.A. LL.B. student at Gujarat National Law University, Silvassa. Her academic interests lie in Intellectual Property Law and IBC. She has interned at the Centre for Trade and Investment Law (CTIL), the Supreme Court of India, the Allahabad High Court, and the Human Rights Law Network. Additionally, she has co-drafted public interest litigation regarding acid sale regulation.
**Prikshit Rathore is a III-year B.A. LL.B. student at Gujarat National Law University, Silvassa. His interests span international trade law and political economy. He has interned with the Centre for WTO Studies, the Centre for Trade and Investment Law, and the SAARC Secretariat.
**Disclaimer: The views expressed in this blog do not necessarily align with the views of the Vidhi Centre for Legal Policy.