Before we talk about 'Smart Cities', let us first understand what makes cities so special. Why are cities the engine of modern growth? Why is it that even though the world has changed so much, the ranking of different cities has largely remained the same, for hundreds of years, for any nation or region? While there are several reasons for the same, the biggest reason is the basic economics of Demand & Supply and the formation of a "virtuous cycles". Due to higher purchasing power of people in cities, as compared to their surroundings, the demand for goods & services is higher, leading to corresponding higher supply. The higher supply of goods & services are largely met either within the city or its immediate neighbourhood (the Power of Proximity rule). This virtuous cycle results in higher job creation leading to migrations from rural areas to cities. Increasing wealth in the hands of a large percentage of diverse population, leads to higher revenues with the local government which in turn leads to higher investments in non-excludable common goods (such as infrastructure), better law & order and an inclusive political system. In this way, several virtuous cycles are created in a city. Moreover the bigger the city, the stronger and larger are the virtuous cycles. The city ecosystem is so strong that it is able to withstand dictatorships, wars, famines, technological changes, economic changes etc. by continuously evolving and adapting.
'Smart Cities' is the latest buzzword in India, ever since the formation of NDA government and the promise of 100 smart cities. However the basic idea of the State being actively involved in fast-tracking the natural evolution of brown-field cities or creation of new green-field cities, is very old and popular. Various kings/queens in the past have tried to create new capitals/cities, with mixed results. In India, Fatehpur Sikri and Daulatabad are the prime examples of spectacular failures, even after huge investments by the State. Jawaharlal Nehru wanted to create scores of modern planned cities, unfettered by the past. Chandigarh is the prime example of Nehru's vision. Various communists/soviet governments in the last century spent huge resources in trying to create green-field cities. However creating a city ecosystem from scratch, with multiple virtuous cycles, is extremely difficult. The number of failures have been far more than the number of success stories.
There is no standard definition of a "Smart City". Broadly the smart city solutions across the world, have focused on the following domains - Infrastructure, e-Governance, Transport, Basic Amenities, Security, Waste Management, Healthcare, Education etc. Most experts agree that creating a Smart City is more like a journey rather than an end goal. I am not going to try to create my own definition of Smart City or create a new framework for understanding/analyzing it. There are enough research papers and articles on it. However I would like to point out one important and key difference between the modern concept of Smart City and earlier attempts (mentioned above) of creating planned brown-field or green-field cities. The key difference is the role of digital technologies, digital infrastructure & related concepts such as Big Data, Internet of Things, Predictive & Prescriptive Analytics etc. While the scope of 'Smart Cities' definitely includes a lot of other things, it is the digital infrastructure, digital technologies and using IT as an enabler to solve various problems, which makes its potential so huge. In this blog post, I will be focusing on these only.
For all the buzz surrounding 'Smart City' in the world, the success so far has been rather moderate for both brown-field and green-field cities. Though few people will doubt the huge potential of smart city initiatives, the on-ground implementations have not resulted in the expected efficiency, cost-reduction or usage. Citizen portals & mobile apps of city corporations for making complains, requests, bookings etc. are a good example. Their usage is less than 1% of the total population, even for the best cities in the world such as New York, London, Berlin etc. The apps/websites for public transport systems are only marginally better. Smart metering & billing solutions for electricity, water, gas etc., have been successfully implemented in several cities, but they have not had the expected change in user behaviour. Same is the case for smart initiatives in Education and Healthcare sectors, which have very low usage. Video analytics have been successful only in a few cities such as London. Same is the case for sensors, which generate a huge amount of data but their practical usage in decision making have been very low. Smart city solutions were supposed to bring high efficiency & savings, through strong feedback loops and help generate insights by combining learning from diverse systems. The most disappointing aspect of smart city initiatives so far, have been that different successful system have not able to talk to each other or learn from each other.
Implementing smart city solutions requires active cooperation of multiple government departments and a central coordinating agency is required to be created for the task. Ministry of Urban Development, India is creating a special SPV (Special Purpose Vehicle) company for each city, to plan, align incentives, get initial buy-in from all agencies, appraise & release funds, implement, manage, operate, monitor and evaluate the Smart City development projects. Historical evidence suggest that it is very critical to make one IT vendor responsible for overall product management of the entire suit of smart city tools. This chosen smart city IT partner of SPV, must be responsible for handling project management and coordination with all the other companies and for developing customized middle layers. Without a capable smart city IT partner, investments in separate stand-alone systems/tools lead to either very poor integration or painful deadlocks & delays.
For any city, there are multiple levels of governments such as city-level (municipal), state-level and federal/national level. Their jurisdictions are separate, their budgets are separate and they are independent of each other. Many times they are controlled by rival political forces. In such a case, it is quite natural that there is lack of cooperation & planning between them. In citizen's mind through, "the government" remains one entity. Having multiple independent and unrelated customer counters, websites, portals, apps, customer care numbers, collection centres and other citizen touch points, results in low awareness, low usage, high cost and high dissatisfaction with each of them. The high level design principle for any smart city, must be to try and have, as far as possible, uniform & integrated citizen facing front-end system(s) - single window/counter for all city issues, single city website, unified mobile app with sub-apps for different services, unified smart city card etc.
The same design principle must be applied for creating front-end system(s) for all the different departments (such as urban development, environment, transport, water, medical, power/electricity, PWD, education, police, public grievance, resident welfare societies, etc.). Government departments are independent of each other and they do not want to deal with multiple tools or any additional processes or IT settings which are not directly related to their narrow scope of work. Hence there needs to be a consolidated and integrated home page, with links to all relevant tools, especially customized for each department. Creating a single login across all tools on the main home page for a department, is highly desirable but not always possible. All the IT complexities between the customer facing systems and the department facing systems need to be taken care by different smart city solutions, customized software and smart process engineering. Department hierarchies, functions, jurisdictions, rules & regulations are different for each city. Hence off-the-shelf products do not work and a majority of smart city solutions need to be custom developed for most cities. Moreover even if off-the-shelf products are used, they can hardly ever be updated to their latest version over time, given the complexities of the overall system.
Making even a very small change in the standard processes of any large sized department is very challenging. This is especially true for government departments which have a huge legacy/old issues and are constantly under the scrutiny of Judiciary and auditing agencies. Moreover in case of smart cities, the change need to be driven by an outside agency which is even more challenging. It is far easier and cheaper to make changes in software suite, even if they have to be reversed later on, rather than make any change in the existing processes of any department. No smart city solution has the luxury of starting from a clean slate (not even for green-field cities or private cities). Hence proper change management is very essential. The key is to have only very small incremental changes and to make sure that all open and legacy issues of the old system are carried forward with each incremental change. Any solution which will not take care of all pending legacy issue of all impacted departments, at each incremental step, will fail miserably. The process changes must be small and frequent and must be very carefully planned and monitored. If there is more than 5-7 weeks gap in between any two incremental changes for a department, the compliance level to the latest change goes down drastically. It is very essential to keep re-enforcing the complete long term vision and how it will help all departments in the end, when implementing each incremental process change.
Given the dynamic nature and pace of innovation in the smart city domain, it is impossible to come up with a comprehensive list of all requirements at the beginning of the contract. While the citizen facing requirements don't change very frequently, the department specific requirements change very frequently (sometimes due to new regulations, judicial decisions, RTI requests etc.) and need to be fixed very quickly. Hence it is extremely crucial that the turnaround time, for new 'Change Requests' to vendors, is very low (approx. 3 days). The initial contract for all vendors need to be very carefully drafted. It has to be a mix of milestone based and effort based contract. The formula(s) for pricing future change requests must be defined in very unambiguous terms for each vendor.
The real benefit of smart cities tools and big data analytics comes when all the different smart city systems such as complain/request ticketing system, billing, collection, asset management, websites, mobile apps, call centers, CRM, sensors, command centre, video management systems, GIS, energy/water meter monitoring systems etc. are strongly inter-connected and use the same underlying data layer. The underlying data layer can be logically separated into two categories - entity-based (citizen database, department employee database etc.) and GIS-based (housing database, camera location database, electricity grid, water pipeline grid, road & sewer network etc.). The cost, both monetary and performance, of creating customized software to interconnect different systems is quite high, but very essential and unavoidable.
Data consistency is a far greater challenge for smart city solutions unlike any other software implementation. There are huge data errors (missing data, wrong data, formatting issues etc.) in all legacy stand-alone systems. Proper handling of all inconsistencies during one-time data transfers from legacy system is very challenging. Also for most of the smart city solutions, there is never a clean one-time transition from one system to another. Maintaining data consistency during long and multiple transition periods is important. Implementing smart city solutions will always involve multiple data clean-up exercises at different stages of implementation. Without advance manpower planning, periodic data-cleaning exercises will become a big bottleneck in implementing smart city solutions.
Citizens physically interact with government departments (municipal, state or central) only when they have a particular need such as paying electricity/water/gas bills, getting NOC certificates, registering a complain/request, booking government amenities, buying or renting a new apartment etc. All these touch-points should be used to add/update the same back-end city resident database, especially photographs. All forms, that are required to be filled by the customer, at each of these counters, must be pre-filled with the personal customer data, as available in the database. Pre-filling form and asking customer to correct any mistakes, is the most in-expensive way of database cleaning and pro-actively updating city database of changing mobile numbers, address, email-ids etc. One of the big advantages that Indian cities have over many other cities in the world, is the availability of Aadhaar database, which ensures that the duplication error is only possible for corner cases, where linking with Aadhaar is not possible.
A significant percentage of human dwellings in any city are either temporary or illegal or under ownership dispute. There is no unique number or identifier given to each human dwelling in a city, similar to Aadhaar numbers for every person in India. All legacy systems have a unique, non-standard and non-compatible way of storing addresses. However the address list in the electricity billing module for any city, is a very good substitute, which covers almost all human dwellings. Anything which is left can be clubbed under 'homeless' category. Electricity bill address database must become the address data layer for all smart city solutions. Data clean-up exercises need to be taken to make sure that address field in all other databases such as water billing, cooking gas connections, landline bills etc. are mapped to a unique smart city address as far as possible. The smart way of doing this is to make the residents do the change themselves when paying different bills online. The more difficult part is to save latitude and longitude for each address. This remains a manual door-to-door effort.
Even though we can get a fairly accurate database of residents in a city and all addresses in a city, the mapping between the two is almost impossible to maintain, especially since a majority of population lives on rent under formal or informal agreements. Similarly mapping residents into distinct families is impossible to maintain. These mappings should not be a part of the basic data layer to be used in all smart city solutions, but should rather be left to each application which needs this information. Private cities where all apartment are sold by a single (or a few) companies, can maintain a much more accurate databases. Through proper planning of NOCs for resale & tenant registration process, they can track addresses of both owners and tenants. This does have a major advantage in creating customized applications for citizens on top of smart city software layer.
One of the most basic smart city solution is a ticketing tool for all non-emergency services in the city, such as complains, request, amenity booking, events registration etc. In many cities in USA, these are called 311 services. In India, most people prefer to physically go to government offices for their problems. They don't trust that registering complains through call center, official website or official mobile app, can get their problems solved. Complain counters in government offices or call centre have a very high operating cost and are highly inefficient in accurately recording the actual customer need for back-end fulfilment teams. Citizens are not good at typing the exact problem and hence they should be allowed to voice record their issue and subsequent comments on those tickets. To avoid the problem of tickets been marked resolved, without actually solving the issue, getting confirmation code from the ticket raiser, must be made compulsory for most cases. It is surprising that such simple common sense features are missing in most smart city solutions in the world. Of late there has been a growing tendency to use social media (especially twitter) to get the attention of governments. Modern smart city ticketing tools need to have plugins for popular social media sites as well. No citizen facing work that gets done by a department, should be allowed to by-pass the ticketing system, else the ticketing system cannot be used for measuring performance of departments resulting in a failed IT project.
Setting up and managing CCTV camera network is very costly, with very low returns on investment. As the number of cameras increase, it becomes virtually impossible to monitor them in real time, even when advanced video analytics are used for generating alerts. Image processing technology still hasn't matured enough, especially for countries such as India with high population density. The biggest disappointment with CCTV network is that in many cases, it is not even able to help ex post facto, as the camera was damaged or there was a connection problem with the fibre optic network or there was an obstruction in front of the camera or the resolution was too poor to be of any use etc. A good solution to this maintenance problem is a video management system which automatically creates tickets in case of any issue with the camera and shows the location of the faulty camera on GIS maps in the command centre.
The number of types of sensors have increased dramatically in the last few years. Commonly used sensor by cities, are sub-station monitoring sensors, gas leak sensors, fire alarms, water flow sensors (both drinking and flushing), parking sensors, street-light sensors etc. One of the biggest challenge with sensors is to keep the number of false or non-actionable alarms to a minimum, by correctly configuring/calibrating them. This takes a lot of time and effort. It is essential to separate warnings from critical alerts. Many sensor implementations fail to make any difference because of the sheer volume of low priority alerts on the dashboard, generating multiple alerts for the same issue and lack of a short SOP for dealing with each type of alert. All sensor inputs must map to only a few common screens (city GIS maps) on the command centre.
In many cities there are completely non-personalized smart cards for various public transport systems (E.g. Delhi metro smart card). In most cities one card is used at multiple transport systems, making payments at various merchant locations, making online payments, loyalty programs etc. Non-personalized cards makes administrative tasks easy, but have a very limited account balance limit (only Rs. 10,000/- in India) and cannot be used for a number of other applications. Oyster cards in London or Octopus card in Hong Kong are great examples of personalized contactless smart cards for all residents of a city. Apart from payments, such personalized cards can also be used for access control for commercial and residential buildings, implementing fines & penalties etc. The long term goal for smart cards should be to have only one unified card for the entire city which is linked to as many applications as possible. Printing photograph, full name or any other personal detail on the smart card, makes the issuance process very difficult, costly & can lead to customer inconvenience. The technology changes in contactless smart card domain are very rapid (there are 8 categories of MiFare cards alone) and backward compatibility is not always guaranteed. There are multiple types of POS devices, turnstiles, access control devices etc. that need to be compatible with the smart card. It is a challenge to make sure that all systems & applications, using the smart card, are upgraded to the newer technology, after every 5-6 years.
It is not possible to cover implementation challenges & learning for all the different smart city domains in one blog post. Smart city solutions in education and healthcare domain have little or no integration with the rest of the solutions. Other smart city solutions such as utility billing, paid parking, smart traffic lights, fibre optic based metering, IOT applications, big data analytics etc. are tightly coupled with each other. Apart from creating these basic smart city solutions, an open-to-all free smart city platform needs to be developed. The platform should enable anyone to use the APIs and data exposed by the smart city platform, to develop their own applications, tools, analytics engines, research papers etc. In this way smart cities can crowd-source ideas, incubate start-ups and co-create application with a large world-wide developer community. A good example to emulate is Singapore’s open data policy[1] and one map[2] initiative.
Effective, timely and detailed citizen communication is very important for successful implementation of smart city projects. Traditional marketing medium such as billboards, print, television & radio are not sufficient. To get effective feedback from early adopters (NGOs, active citizens, 3rd party contractors etc.), two way communication medium such as discussion forums, email groups and social media, needs to be adopted. For any effective communication strategy, smart cities must have a fairly accurate (it can never be 100%) database of email-ids and mobile numbers mapped to each citizen. Smart cities cannot rely on citizens informing them when their email-id or mobile numbers change. A permanent call-center is required to continuously call or email citizens and proactively keep the database updated. Every time a communication message by any smart city application to an email-id or mobile number fails, they must be added to the list of faulty email-ids or mobile numbers that need to be corrected.
Smart city applications and tools stack on top of each other. Certain basic applications and data layers need to be developed first before the rest can be built. However the exact sequence, in which applications/solutions must be developed and implemented, should vary from city to city based on the needs of the specific city. For example there is no point in having a smart card, if you don’t have a ubiquitous public transport system(s) in the city. In cities where the population is less than 20k, smart city systems such as RFID tags parking systems, smart water meters etc. will not result in appropriate return on investment. The smart city solutions which solve the most pressing need/concern for the citizen of that city must be prioritized over others. The need can be security (especially for new green-field cities) or transport or governance (for brown-field cities).
As mentioned earlier, cities flourish because of virtuous cycles of high demand & supply within and around the city. The city must provide jobs and all basic minimum resources, which will then attract others to migrate to the cities. Very often city planners neglect the aspect of job creation within the city and give over emphasis on creating amenities. Moreover they focus on malls, shopping complexes, hospitals, colleges etc. but neglect basic facilities such as last mile transport (auto, rickshaws etc.), schools, play-schools, crèche, laundry shops, household helps, local medical centres, groceries, electricians, plumbers, local wine shops etc. Many of these basic amenities require high subsidization at the initial stage. Investors in housing projects, who do not wish to live in the city, are a huge risk in creating city ecosystem. If the right city ecosystem is not created, it will end up creating ghost cities such as Kangbashi and Thames Town in China. New suburbs (such as Bandra Kurla Complex, Mumbai) or cities (such as Greater Noida) existing close to an old city are highly dependent on good and multiple connectivity to the old city. Independent green-field cities (such as Amravati) are highly dependent on governments to create new jobs and kick-start migration into the cities. Smart city solutions can only act as an enabler for achieving higher efficiencies, but they cannot be used to create city ecosystem. This is the reason why most of the smart city solutions work better for existing cities rather than new cities.
Once a smart city solution has been successfully deployed, monitored and stabilized, it needs to be handed over for operations to the respective departments, except the department for data correction which need to remain centralized across all smart city solutions. Some solutions such as waste management, smart electricity & water meters etc. come fully under the domain of a single department and cost/benefit allocation is very simple. However most other smart city solutions such as smart card, mobile app, website, GIS systems, RFID parking solution etc. cut across multiple departments. Special accounting mechanisms have to be developed to distribute revenue, manpower required, operational costs etc. of these solutions across departments and governments.
Even through currently the ROI (return on investment) on smart city projects do not meet expectations, I have no doubt that investments in smart city projects will only increase in foreseeable future. Many companies will come up with products which are specially customized for city use cases and not corporate use cases as most IT products are currently. The recent surge of small townships and private cities built by private developers in India, will lead to greater development of smart city applications, as decision making in a private company is always faster than any government agency. There are several other aspects of smart cities that I have not been able to cover in this blog, especially non-IT related areas. In this blog I have mostly tried to cover aspects of smart city which are different from traditional city planning. A lot of work needs to be done before the dream of 100 smart cities in India can be realized. I am eagerly looking forward for the day when I can enjoy most of the smart city solutions described above myself.
