Role of Geospatial Systems in Making City Utilities Efficient and Cost-effective

Geospatial systems, in convergence with modern ICT, can help city utilities become efficient, consumer-friendly and cost effective.

The management of cities involves the management of utilities, which are essential to keep a city running. Utilities are like the nerves and veins of a city. This fact was realized many years ago, as cities grew into megalopolises. CAD and databases came to the fore to form AM/FM (Automated Mapping/Facilities Management), a key component of utilities management. The advent of GIS-enabled integrated management of maps and attributes, and most importantly, map analysis, visualization and decision support, was a huge step forward beyond CAD-based solutions. With the introduction of new data collection technologies like high resolution satellite imagery, digital aerial imaging, LiDAR, Ground Penetrating Radar and GIS integration with SCADA and ERP, the management and operation of the complex network of assets and utilities has become more sophisticated and much easier.

AM/FM/GIS Data and Integrated Functions | Source: “Geographical Information Systems”, 2nd Edition, Paul A Longley et. al. pg 805

Modern utilities management

Modern utilities management encompasses transportation, electricity, gas and water distribution, street lighting, solid waste, stormwater and wastewater, and communications. If there is a network connecting various assets and providing a service to the public, then it is a part of utilities. It could be publicly owned, like by a municipality, or privately owned, like by a telephone service provider.

Role of geospatial systems

A typical city has some or all these utilities. To make the city smart, these utilities need to be augmented with real-time and near real-time data and analytics, which can provide decision alternatives to support management of the facilities comprising the utilities. Geospatial systems are already part of the AM/FM systems, but apart from mapping the city and its network of on-ground and underground utilities and assets, these systems can be used to provide real-time monitoring and management of utilities and services by integrating other data sources and services.

For data acquisition, several systems exist — high resolution satellite data, aerial survey data from imaging sensors and LiDAR are well known. The advent of drones makes such data collection easier and timely, particularly to track changes in a rapidly growing city and also for rapid action in times of disaster. The availability of smart sensors in the form of IoT devices greatly enhances the acquisition of in situ data. Opportunistic data in the form of anonymized smartphone locations, social media posts and volunteered information add to the data stream.

Data management

While the base data is amenable to GIS, the rapidity with which both spatial and non-spatial data is growing and the addition of high velocity and transient data coming from IoT sensors and other sources makes simple AM/FM/GIS solutions inadequate. Hence cities are increasingly moving towards integrating modern ICT systems like Cloud, Big Data and Blockchain.

Big Data

Structured and unstructured data collected from diverse sources and used as an ensemble to derive information is referred to as Big Data. These datasets can range from tera to petabytes and beyond. In the modern interconnected digital world, there are enormous real-time data streams from various sources like mobile phones, credit cards, RFID devices, sensor data, chatter on social networks. Big Data is characterized by the four ‘Vs’ — volume, variety, velocity and veracity.

The key to Big Data is the need to look at all data in ensembles, specific to applications. Thus, Big Data also includes data intensive computing, middleware, analytics and scientific and social applications. A typical Big Data system, City Data and Analytics Platform (CiDAP) has been implemented in the Spanish city of Santander. The system manages historical data, near-time data and also real-time data such as data from fixed sensors like parking sensors, traffic sensors, and light sensors, as well as moving sensors attached with cars and buses. The unstructured data can be texts collected from social networks and images/video collected from video surveillance systems deployed in cities. Extensive use is made of Cloud data services in the project.

Geospatial systems have always made the best use of modern ICT systems and utilities. Cloud, IoT, Blockchain, Big Data Analytics and Artificial Intelligence will feature strongly in the future utilities planning, execution and management


The ‘chain’ in Blockchain is the chain of transactions in the form of ledger entries about assets which could be money, imagery, data, maps, documents, etc. In reality, what is actually transacted are tokens containing the metadata of the assets. The actual physical transfer happens separately. ‘Block’ refers to the grouping of transactions related to each other. A way of looking at Blockchain is to consider it as a ledger where all transactions are entered.

Blockchain can make the monitoring of networks, assets status and transportation efficient. In terms of utilities, three major areas where Blockchain can be used are transportation, energy and waste management. Blockchain results in decentralization, improved security and interoperability of systems. Supply chain management ensures safe and reliable transportation of goods, particularly perishables and medicines. IoT sensors can interact with Blockchain to enable energy load balancing and monitor waste management


Many compute and data intensive applications have moved into Cloud platforms. From a client perspective, the key aspect of Cloud is the ability to access Cloud facilities on-demand, without managing the underlying infrastructure and dealing with the related investment and maintenance costs. For utilities, Cloud can be used to develop proprietary software using PaaS (Platform-as-a-service) or use available solutions, like Salesforce under SaaS (Software-as-a-service). DaaS (Data-as-a-service) can be used to aggregate data from different sources like geospatial data, IoT sensor data, customer data, client data, transactions data, volunteered data, data from social media, etc.

Data management hierarchy

Big Data, Blockchain and Cloud are all part of the overall data management system. A system called the Computer Integrated Management (CIM) enables the distribution of data relevant to each level of management. At the apex of the CIM is the Enterprise Resources Planning (ERP) which lays down the overall plan for the utility management. The Manufacturing Execution System (MES) manages the detailed planning as per the ERP plans. The Supervisory Control and Data Acquisition System (SCADA) is self-explanatory and at the lowest level are the various sensors and other raw data sources. These data sources produce a variety of data which may lack standardization, particularly Big Data which, by its very definition includes unstructured data.

The Open Platform Communications-Unified Architecture (OPC-UA) provides the means to manage these data sources and provide a secure integration with different platforms, and secure transfer of data from sensors to the various levels of the management pyramid from SCADA to the enterprise level.

System Architecture of the CiDAP Platform | Source: Bin Cheng,, “Building a Big Data platform for Smart Cities: Experience and Lessons from Santander” 2015 IEEE Congress on Big Data

Use cases

The management of utilities may use one or more of the technologies and data sources as described above. While AM/FM/GIS forms the basic data layer, the day-to-day planning, implementation and servicing may vary from utility to utility. These variations are illustrated through the following use cases.

Electric power generation and distribution
The use of GIS for management of electric power generation and distribution activities is well established. In a competitive market, operational efficiency and cost reduction are a given. Going beyond establishing new markets, planning, building, monitoring and managing power generation and distribution, the market has to factor in new technologies like smart meters and distributed power generation from solar panels. Management of power generation and transmission requires a reliable communications system and an instrumentation overlay that senses, records and transmits crucial parameters. Big Data analytics in this scenario is a given.

In Boulder, Colorado, smart meters enable remote reading of power consumption and also allow customers to log in and check their power usage. Industries can plan to shift their peak loads to lean periods. In Bangkok, an experiment is underway where individual homes in a community have invested in renewable energy sources and have become ‘prosumers’, consuming and trading their energy generated.

Oil and natural gas
Kaare Helle, Innovation Manager, DNV GL-Oil & Gas, writes in Pipeline Technology Journal that some of the key digital technologies influencing the pipeline industry are decentralized energy transactions, metering and billing on Blockchain. Artificial Intelligence/Machine Learning can be used to enhance forecasting models and gain new insights into large operational asset datasets. Data platforms can be used for data sharing between asset owners, operators, regulators and investors. Enhanced safety can be achieved through the use of drones for pipeline inspections and monitoring using satellite data.

Field-based workflow and automated data collection can be standardized using connected mobile devices. Big Data and analytics and Machine Learning can help in benchmarking of asset performance across large numbers of diverse assets. Models can also be shared between stakeholders to enhance cooperation. Finally, Digital Twinning can help in making remaining life calculations and failure and reliability forecasts.

Urban mobility
The rapid growth of cities and the preponderance of privately owned vehicles has led to traffic jams, pollution and inefficiency. Modern public transportation facilities must be intelligent and multi-modal, have smart traffic signals and pollution monitors. The city of Los Angeles uses magnetic sensors and video cameras to monitor traffic and synchronize 4,500 automatic signals, which has reduced traffic congestion by 16%.

Seoul, Singapore, Yokohama and Barcelona have smart transport systems which stress on walking, cycling and public transport as the primary means for mobility, with personal motor vehicles being actively discouraged. There is a need for dedicated cycling tracks. Many cities are integrating shared cycle facilities which connect to rapid transit systems like MyByk in Ahmedabad and Velib in Paris.

Rapid transportation routes, without signals, need under and over passes, ring roads and city bypasses, which need to be built into road and rail networks. This has given rise to dedicated facilities like Rapid Transit Systems for road and BRTS and Metro Rail for rail.

Modern mobility solutions, particularly electric cars, ride-share and driverless vehicles require real-time data. Electric vehicles have become a reality and driverless vehicles are beginning to arrive. A network of charging facilities and up-to-date road information systems need to be developed for these types of transportation systems. A typical system based on a Cloud architecture, which is integrated with ISP facilities, has been proposed by the Fraunhofer Institute for Open Communication Systems (FOKUS), Berlin.

Water supply
Efficient supply of quality potable water with minimum loss is the aim of a city’s water management. Some of the methods used are installation of sensors to monitor water flow, water usage and water loss on a real-time basis. Systems are used to optimize water usage, as well as to attend to leaks. The city of Long Beach, California uses smart water meters to help detect illegal water usage and optimize overall usage — customers can reduce water use by 80%.

An interesting concept on the use of a multi-agent system for maximizing service levels while minimizing cost based on advanced forecasting techniques like ARIMA (Autoregressive Integrated Moving Average) and neural networks has been developed in the University of Oviedo at Gijón. The proposed system not only minimizes the volume of water used to satisfy the demand, but also reduces the energy consumption in the work of collection, purification, distribution and purification of water. The model addresses long-term prediction (annual demand forecast), midterm prediction and short-term prediction and even hourly predictions.

The main issues of sanitation are sewerage and solid waste management. Many cities are adopting a decentralized system of wastewater treatment, ensuring that the water can be reused for non-potable purposes — thus saving a scarce resource. Where treated wastewater flows into waterbodies, it is necessary to monitor its quality to ensure that the effluent is safe.

Management of solid waste involves timely collection and disposal. Songdo, South Korea has an automated solid waste collection from individual homes via a network of pipes. The solid waste is then sorted, recycled or buried. In Porto, Portugal, IoT sensors are used to track the load in dumpsters and schedule trucks to periodically carry away filled ones with empty dumpsters.

Internet and telephone
AM/FM/GIS systems are being used by wired telephone service providers to map out their network and assets using CIM services. While Internet over wireline networks has been around for long, the latest is the use of optical fiber to home technologies which run in parallel to the wireline network.

Wireless telephony services began with Wireless in Local Loop (WLL) to serve clients with short-term requirements or limited mobile requirements. Full mobility had to wait till cellular systems were developed. Cellular services have progressed from 2G to 4G and now to 5G. The advent of cellular networks has brought in a new kind of network of wireless towers and the associated software for managing mobile clients. These networks are primarily urban in nature but do provide connectivity along major trunk routes.

Wireless networks have gained importance in far-flung areas where providing wireline or optical fiber could be 20 times more expensive. Connectivity solutions for such regions are through VSAT providing satellite backhaul to connect to the main network.

One of the big users of wireline and wireless communications networks are IoT sensors, which are used in most of the utilities discussed in this article.

Future of utilities management

GIS-based AM/FM will continue to grow with the availability of more versatile imagery data from satellites and aerial platforms. Geospatial systems have always made the best use of modern ICT systems and utilities. Cloud, IoT, Blockchain, Big Data Analytics and Artificial Intelligence will feature strongly in the future utilities planning, execution and management. New business models will evolve as new technologies mature, which will lead to higher efficiency and cost-effective solutions. Utilities will increasingly be decentralized and will become more user-friendly and interactive, enabling consumers to optimize their usage of the services.

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