Intelligent street lights illuminate new applications
by Kishore Jethanandani
Smart cities have evolved beyond pilot projects testing digital services to the delivery of networked digital services. Their new pivot is multi-use platforms that integrate several data streams that are leveraged to improve the city’s infrastructure.
Street lights, for example, present an opportunity to create data networks by using each pole as a node to gather data, from a cluster of local devices, and feed them to several applications and platforms for generating services.
San Diego reflects an emerging trend of using street lights in a pervasive computing and networking system.
“The replacement of aging street lights with LED lights not only created an opportunity to significantly lower energy costs but also to gather data by making them aware of their surroundings with audio, video and environmental sensors,” David Graham, deputy COO of San Diego, said in an interview with Telco Transformation.
Smart cities are also supplementing government grants with surpluses from energy savings to be able to fund larger projects.
“Private sector companies, with legal protection from energy savings performance contracts, are willing to make the initial investments in street lighting because cities agree to share the huge savings realized from the lower energy consumption by LED lights,” Ryan Citron, research analyst at Navigant Research, told Telco Transformation.
Data gathered from HD cameras installed on street lights also has transportation applications that help to optimize the timing of traffic signals at intersections to minimize congestion.
“Currently, we have adaptive signaling for traffic flow management at 30 intersections,” said Graham. “The data from the sensors on stop lights is analyzed to decide the intervals at which stop lights change. With the use of AI, we can make the street lights more adaptive not only by events but also the length of queues, holidays and many other variables. We have been able to reduce queuing by 40% in one of the corridors.”
The growing scope of smart cities applications has created many new possibilities in improving a city’s infrastructure, but it has also created a dilemma for city network administrators. While their ideal choice for a network is fiber optics, this option can be cost-prohibitive for the current bandwidth needs of cities. Other popular low bandwidth and cheaper networks, like SigFox, are useful for microdata but could impede the future growth of higher bandwidth smart city applications.
Furthermore, multiple applications, consuming varying volumes of data, are built on top of a common platform. The data is not only for vehicle traffic management but also smart lighting to save energy, event and emergency management, smart parking, air quality monitoring or uses as varied as easing eye strain by changing the color of LED lights, crime prevention, surveillance, predictive failure notification, etc. Flexible networking is needed to route traffic cost efficiently, and meet service quality standards for a broad variety of applications.
Some solution providers improvise with help from analytics and make do with the least possible bandwidth in the short term.
“Analytics embedded in the cameras on street lights transmit only the results of the query requested for traffic management such as counts of traffic in a specific lane. Since the traffic flow in a region is interrelated, we can use the traffic data from the queries and pre-determined correlations between them to estimate the expected impact on traffic at proximate intersections,” Sohrab Modi, CTO and SVP of Engineering at Echelon, told Telco Transformation. Accurate estimates are achieved only after training the algorithms on a great deal of data.
A study conducted by Navigant Research “analyzed a dozen connectivity technologies and their suitability as a smart street lighting/city platform” and identified medium-band networking solutions as the best option for balancing cost and support for the most “high-value smart city applications.”
PLC, a medium-band network, has been widely used in European countries because it provides network connections on powerlines already connected to street lights and saves on upfront capital costs. In combination with RF-Mesh, a peer-to-peer wireless network, it maneuvers around obstacles such as tall buildings. PLC is less flexible being hard-wired, but that also makes it more secure.
Narrowband options like LPWAN are very inexpensive and have long battery life but by themselves cannot serve the needs of several applications. Carriers are launching NB-IoT and LTE-Cat-M1 which provide the security of licensed spectrum while the other narrowband networks use free unlicensed spectrum. Broadband connections like 3G and 4G are ubiquitous and can serve the bandwidth needs of multiple applications. WiFi is a cheaper broadband network because it does not use licensed spectrum and it can aggregate traffic from several devices.
Smart cities can prepare themselves for their future needs by subsuming these networks into an overarching software-driven network with centralized controls. The intelligence of centralized controls will help to route traffic to any of these networks depending on the needs of individual applications and their users.
Smart cities have learned to build the foundations of intelligent services that can serve a variety of needs valuable enough for consumers to be willing to pay for them. As more services are offered on the same platform, the incremental costs of each of them decline. Software networks will keep the costs of network expansion low by making the most of the capabilities of networks already in place, and city administrators can future-proof their networks and focus on creating the environment for more innovative services.