Authored by Mr. Sameer Bhatia, Director of Asia Pacific Consumer Business and Country Manager for SAARC & India, Seagate Technology
In a move towards improving women’s safety in the city, Delhi government recently announced installation of 150,000 CCTVs in residential and commercial hubs across national capital region. This is an addition to the 140,000 surveillance cameras that the government is already in the process of installing in these areas. While cities like Delhi have long depended on video surveillance to enhance public safety, today’s smart cities are harnessing those solutions for a multitude of citizen-centric civic purposes, including traffic management, lighting, parking enforcement and more.
This is due in large part to the fact that cameras themselves have become intelligent computing devices that offer video analytics and the ability to integrate with disparate systems and devices. Among the many potential applications for which surveillance and other data can be combined for smart city applications is transportation. By deploying surveillance cameras with object detection and recognition analytics, officials can automatically detect stalled cars, wrong-way drives and other obstacles that can impact both safety and travel times. Using this insight, cities can use traffic management and/or digital signage systems to alert drivers to potential issues and reroute them to avoid these obstacles.
This is just one example of how municipalities can implement smart city platforms and technologies to achieve these goals. At the heart of these systems are the solutions used for storing all this data. Below are some key factors and best practices to consider when evaluating these solutions, which are the foundation for smart city applications.
Tying it all Together
According to IHS Markit, the amount of data generated worldwide by surveillance cameras alone is expected to reach 2,500 petabytes per day in 2019. A case in point is the imminent installation of surveillance cameras in the fleet of NCR’s buses. The city already has a widespread rapid transit system – Delhi Metro, which stretches 373 KM and is covered by over 9,000 CCTV cameras. With round the clock monitoring, these cameras are bound to generate a tremendous amount of data. However, the true value of this data lies in the ability to aggregate and analyze it in order to provide a fuller picture of overall transport operations and detect any dysfunction or malicious activity.
While enhanced by artificial intelligence (AI), today’s surveillance solutions are capable of providing the kind of actionable insights and intelligence smart cities require. At the heart of these applications are surveillance storage solutions, which are capable of aggregating all this data both at the edge for immediate analysis and real-time intelligence as well as in back-end environments for long-term analysis, overall trends and deep learning analytics that make the system smarter over time. These robust solutions are built to withstand the rigors of smart city applications and deliver a number of other features that in turn benefit municipalities.
Finding the Best Storage Fit
In the age of the IoT and AI, where devices are generating more data than ever before, deciding how to properly store all this data has become a critical consideration. Depending on a city’s needs, there are several approaches available, including storage at the edge (close to where the video or data is captured), in the cloud (a large, centralized backend storage server or servers) or even a combination of both, which some experts are calling IT 4.0. For smart cities with hundreds or thousands of cameras and IoT sensors, cities should take a multiple-layer approach to storage architecture that delivers the benefits of both edge- and cloud-based storage.
The main reason for this is that streaming large amounts of video and data to the cloud is expensive and can suffer from significant latency issues. The solution for smart cities is to deploy technologies that aggregate, filter and analyze data at endpoints and at the edge and then have relevant alerts sent to the video management system at the head-end for review and response. This allows data to be quickly processed and notifications to be delivered, which can improve public safety.
For example, when a municipal camera detects an incident using video analytics or AI, it can send an alert to a monitoring or command center, allowing a police officer to respond quickly. A CCTV camera system built with a surveillance-optimized hard drive allows dispatchers or operators in the command center to access video of the incident to further assess the situation, enabling them to provide the officer with real-time situational awareness and actionable intelligence about the incident.
To identify deeper trends, video and data can then be uploaded to the cloud, where providers utilize high-quality enterprise and solid-state drives. This large repository of data collected over a longer period of time can then be analysed for deeper insights – for instance, to identify peak traffic hours and traffic patterns throughout a city, allowing officials to make decisions that can improve people’s commutes, such as synchronizing traffic lights at certain intersections.
Data Security is key
Given the sensitivity of smart city data and the potential ramifications of a network breach, cybersecurity is a paramount concern. Naturally, this means that any camera, device or sensor connected to the network must offer top-of-the-line cybersecurity measures against vulnerabilities. Data can also be stolen from hard drives themselves due to improper disposal. To combat that possibility, it’s important to select drives that offer hardware-based encryption as well as secure methods for erasing data.
To avoid system lapses and drive failures, and the data loss this may lead to, municipalities should ensure there is redundancy in their systems. They must also augment this by subscribing to data rescue or recovery services, which allow data to be recovered for up to two years in some cases. These types of services are especially crucial for law enforcement or other public safety personnel who require data to be stored for lengthy periods of time.
In conclusion, while there is no doubt that smart city applications offer the ability to improve operations in a number of areas to enrich public lives, a robust storage infrastructure serves as the foundation for these initiatives. By following the above best practices, cities can choose storage solutions that offer high performance and reliability, and ensure they are deploying it in the most appropriate way, both of which are key to determining the success of any smart and safe city initiative.