Crowdsourcing data, not opinions, for last mile void in government-people relationship
Data is the new weapon in today’s information rich world. Contradictory to opinions; information is tangible, replicable and context independent. Crowdsourced data has resulted in many great products like google maps, content based social feeds, open innovations, etc. Like any other tool, crowdsourced information also serves the goals of collecting authority. Collected data can be used to force you to buy a certain product or to make a better disease diagnosis. In parallel, my professional training as a designer has helped me understand the value of probes for systematic innovation. The probe can be anything- a piece of art, a photograph, a sentence, a melody, a narrative and more. The importance of a probe lies in making us think, analyse, ask questions and seek answers for them. Openly accessible and well presented crowdsourced data has the power to be an able probe for shaping conclusive conversations in people-government negotiations. With right questions and appropriate methods, collected information can persuade actors of change. Data of the people, by the people, for the people, shall be leading development efforts in the emerging economies.
I will be joining the founding batch of UNLEASH which is a global innovation lab that brings together people from all over the world to transform 1,000 personal insights into hundreds of ideas and build lasting global networks around the Sustainable Development Goals. My aim is to meet amazing, motivated people to discuss opportunities about how new means of crowdsourcing data can assist in sustainable development efforts. I was selected in theme ‘WATER’ for the idea ‘Technological Interventions for Effective Water Network Management’ which has been shaped by my contextual experiences.
I have spent my childhood in an Indian town with a dysfunctional municipal water supply network. The water supply was limited to an hour/day. However, poor pipeline conditions resulted in an effective 50% supply cycle as consumers did not use the initial 50% water fearing contamination from broken pipeline segments. As I read about water conservation in school books, I became very uncomfortable with so much water being wasted around me. However, I could not come up with a suitable solution owing to my limited knowledge. The problem appeared in two contexts:
- There was no accountability for the quality of service. The service provider did not care about infrastructure health and consumer had no means to hold the service provider accountable.
- Pipe inspection technologies were (and still are) very costly and were never heard of in Indian towns. The inspection engineer’s highly specific reports ( and consumers lack of access to them) would have further served the interest of service provider only.
The existing arrangement lacked tools/means of service evaluation and consumer feedback. If people were able to localise the source of the problem, they would have persuaded the service provider to facilitate a solution.
To improve the condition of the water supply networks, I aim at a data driven multi-stakeholder network health monitoring framework. Proposed framework has two parts:
- Cost effective water quality and pipe health monitoring tools for consumers and service providers
- Mutual amalgamation of logged inspection data, a machine learning-based insight generation tool utilising sensor fusion approach and a public platform for assimilation of gathered insights (and raw data)
The proposed tool for service providers is a cost effective passive pipeline health robot which crawls with the flow of water inside the pipeline and collects relevant information about pipeline health and water quality with localisation data. Once out, the data is transmitted to a central server for automated post-processing. Consumers are also provided with an embedded water quality measurement tool which samples the data across the channel and acts as a secondary validation approach. The tool can also be used in complex pipeline meshes where running a crawler is not feasible. The tool also transmits information to the same server as the crawler. Intelligent on server algorithms then generate the actionable insights about health of the entire water distribution network. The endeavour has both technical and functional challenges. However, I am confident that Unleash will connect me to potential partners, teammates and collaborators who will assist me in turning the concept into a reality. If implemented well, such an approach can save 25% waste water in metro cities, 40 % in tier-2 cities and 50 % in towns.
Eagerly waiting to join wonderful people in Denmark!
I am an instrumentation engineer and currently a PhD student at Design Programme,Indian Institute of Technology-Kanpur. My dissertation examines opportunities in amalgamation of established system design methodologies in research space of structural health monitoring. Being nurtured at the boundary of design and technology, I foresee endless opportunities at the horizon of both. My research interests are consumer experience evaluation, mechatronics and nondestructive testing. Some of my conceptual upbringings have successfully secured grants from relevant industrial sponsors. Currently, I am shaping opportunities to design and develop context-aware machines to serve as a research tool in design expeditions.