The Business Case for Smart Street Lighting as the Smart City Network


Marissa Wright

January 7, 2023

This article is intended to provide a supportable, accurate framework to help answer these questions:  “Why should our organization care about Smart Street Lighting? What do street lights have to do with our Smart City vision? 

The Benefits of Smart Street Lighting.

This article is meant for those who build their own internal business cases or read them in the course of their work. If that’s not you, here is the bottom-line:

  • Tondo’s solutions can enable its customers to move lighting from unmetered to metered rates and cut their energy costs by 50% or more. [Jump to Section]
  • Tondo’s Smart Lighting enables cities to deliver standards-based lighting according to demand, resulting in a savings of 70%. [Jump to Section]
  • Network-controlled Smart Lighting has been shown to reduce non-electricity operating costs of managing street lighting by 50%. [Jump to Section]
  • The reduction in electricity use from adaptive dimming also extends the life of LED lamps by 60%-70%. [Jump to Section]
  • To cost-effectively enable a Smart City strategy, cities require secure, standards-based wireless networks for sensors and devices to operate on.
  • Tondo’s Smart Lighting controllers include a secure city-wide wireless network platform that can reduce the cost of sensor and device operations by 60% or more. [Jump to Section]
  • A Tondo Smart Lighting project provides a positive cash flow budget benefit with a 13.8%+ internal rate of return (IRR) and a 4 year project break-even.[Jump to Section]
  • When you add sensors to the Tondo Smart Lighting project, the IRR can triple and increase the recurring annual benefit by 2.7x [Jump to Section]
  • When compared with an LED retrofit project benefit, a Tondo Smart Lighting project provides 85% of the benefits versus LED retrofit, and a Smart City sensor network project can provide 280% of LED retrofit benefits. [Jump to Section]

Additional non-financial benefits of Smart Lighting include:

Tondo’s Smart Lighting system provides a complete and secure Smart City network and IoT (“Internet of Things”) management platform based on open standards and technologies.

Tondo’s standards-based approach enables cities to avoid being locked into proprietary vendor technologies and maximizes the useful life of the Smart City network.

Can Dimming Street Lights Reduce Your Bill?

Although we have had the ability to dim street lights since 1977, it’s not quite that simple.

Lighting is about pedestrian and driver safety – we need standards bodies like ANSI, CSA, and IEC to define the minimum standards that tell cities what is safe. Otherwise we get chaos, risk, and liability.

New standards were developed between 2011 and 2021 that enabled us to deliver safe, standards-based, dimmable lighting. Solutions provided prior to 2021 were based on non-standard proprietary methods that risked both safety and interoperability.

Metered vs Unmetered Electricity Rates

Utilities have typically delivered electricity for streetlighting under an “unmetered” rate for municipalities. These rates assumed that it was impractical to meter individual lights or groups of cabinet-controlled lights, and rates are calculated by the input wattage for a light, multiplied by the number of hours of darkness per month – which assumes “dusk-to-dawn” lighting.

In 2021, the American National Standards Institute (ANSI) published the C136.50 and C136.52 standards [14] for the accurate measurement of electricity of an individual streetlight.

In 2022, Measurement Canada published “E-38—Program for granting conditional permission to install and use street lighting luminaires with adaptive controls without the approval, verification and sealing of their embedded measurement technology“. This provides a process for Canadian municipalities to realize the benefits of new energy measurement technologies such as Tondo’s.

A bar chart describing the difference between unmetered street light electricity rates and metered rates enabled by Smart Lighting that is compliant with ANSI C136.50 and C136.52 energy measurement standards, and eligible for Measurement Canada's E-38 program for metered luminaires.
In this chart, we see a 66.7% cost reduction moving to metered street lighting based on Smart Lighting-enabled technologies.

Energy measurement standards for luminaires are relatively new, and initially, it may require cities, Tondo, and utility providers to work together to ensure accurate savings are fully reflected on municipal energy bills. In the case of BC Hydro rates used in this example, their published Tariff Rate Plan 1702  [2] that governs dimming of customer-owned street lighting requires a dimming control schedule to be submitted in advance for approval, and can only be changed twice per year.

Clearly this is not a tariff that supports standards such as ANSI 136.50, 136.52, or Measurement Canada’s E-38 program. As such, municipal customers and Tondo will need to work with their utilities and any regulatory organizations to support Smart Lighting controls within their rate schedules.

Time of Use (TOU) Billing

Time of Use billing incentivizes utility customers to use less electricity during high-demand periods, and shift their use to lower-demand periods.

TOU tiered rates help the electrical utilities avoid brown-out, black-out, and manage their costs: electricity is a commodity and costs can fluctuate significantly on demand.

Cities require new technologies that can deliver safe, standards-based lighting, avoid wasted light during low-demand periods, AND measure their electricity use accurately to audit and manage their billing.

LED Street Lights Still Use Energy.

It’s highly likely you’ve already written a business case for your LED retrofit project, and it’s either in-progress or completed. The case for LED retrofit is simple: a savings of approximately 34% in energy costs, a 4x longer lamp lifecycle, and a corresponding reduction in lamp replacement truck rolls.

A bar chart comparing the billing wattage of HID lighting with an LED retrofit project for a city with 7,300 luminaires.
Everyone can understand the business case for LED upgrades – a 36% drop in electricity consumption and GHG footprint for street lighting.

Today, most streetlights are controlled by “dusk-to-dawn” photocells or astronomical clocks to detect night-time conditions. The power to a light pole is most often controlled by wiring cabinets that turn the pole power on and off. When the sun goes down, a photocell or astronomical clock tells the cabinet to power the pole and the lights come on.

Lighting standards provide different levels of light according to pedestrian, driver, and cyclist use. This is often referred to as “adaptive lighting” and requires “smart lighting” in order to implement.

Dusk-to-dawn control wastes more than 60% of streetlight energy by providing light when it is not needed.

Street Light Environments are Dynamic.

Dusk-to-dawn streetlight control is not only wasteful, but also delivers sub-standard lighting when it cannot adapt to its environment:

  • There are different types of streets serving different transportation needs: local streets, laneways, primary collectors, secondary collectors, primary arterials, secondary arterials, expressways, and different types of highways [5]
  • Lighting demand changes based on volumes of vehicle, cyclist, and pedestrian traffic [9]
  • Vehicle, pedestrian, and cyclist traffic changes based on time of day, day of week, and the month of the year [15]
  • Lighting demand can change for special or unexpected events
  • Sunrise and sunset times change not only by season, but by latitude and point relative to the equator [19]
  • Weather, pole position, and pavement surface affects the quality of by as much as 240%[17]
  • Intersections and crosswalks where pedestrians and vehicles interact have specific lighting requirements [5]

Lamp luminance output – even with LEDs – slowly degrades over time, changing the desired lighting levels. As a result, lamps are:

  • Replaced earlier than their useful life
  • Must be manually adjusted by dispatching field service calls
  • Lighting is purchased over-illuminated at initial installation to compensate for degradation

None of these scenarios are desirable.

A pie chart comparing the benefits of an LED retrofit project with a Smart Lighting project using adaptive dimming control.
ANSI/IES RP-8-21 standards enabled by Smart Lighting control to your LED street lights can equal the benefits your LED retrofit initiative – and establish a Smart City sensor and device network platform for more than 2.5x those benefits.

In some cases, municipalities have implemented crude dimming levels according to specific evening times managed by an astronomical clock, such as dimming 50% at midnight to dawn. That approach may result in illumination that does not conform to standards and best-practices, and may present a liability for cities.

Smart Lighting control delivering standards-based lighting on-demand offers significant opportunities for cost-reduction and improved lighting conditions.

Solution: “Smart” Street Lighting.

Smart street lighting can adjust light levels according to:

  • Roadway classifications set by standards and regulations, such as North America’s ANSI/IES RP-8-21 and Europe’s EN 13201 standards
  • Traffic, cyclist, and pedestrian volumes
  • Ambient light levels during daylight, dusk, evening, and dawn
  • Weather conditions
  • Intersections and crosswalks
  • Special or unexpected events
  • Other safety and security considerations

By delivering standards-compliant lighting on-demand, Smart Lighting becomes a significant source of operational, maintenance, electricity, GHG savings – and safety.

How Can We Dim Street Lights Safely?

The short answer: by applying the established roadway lighting standards using Smart Lighting controls to roadway and pedestrian demand.

The purpose of street lighting is to provide safe and secure environments for drivers, cyclists, and pedestrians. This is particularly important where they interact with each other. When demand drops, roadway lighting standards allow cities to consider lower illumination levels.

Let’s step through a case using the North American ANSI/IES RP-8-21 standard for roadway lighting and apply it to a city’s real-world data. [1]

This Canadian city has a population of 92,000 people over 20km sq. and has 7,303 street lights with 99.3% of them upgraded to LED lamps.

The chart below shows the city’s share of roadway by ANSI/IES RP-8-21 standard classification type:

A chart showing an example of the diversity of roadway classes within a city of 95,000 people and 7,300 luminaires.
79.2% of this city’s roadways are classified as Local, which will be lower traffic and highly correlated to commuter and shopper traffic periods.

Next, when we look at the vehicle traffic volumes during Dusk-to-Dawn periods, we can also see from this chart:

  • Most traffic volumes are low traffic periods
  • Demand changes for each day of the week

As a result, lighting standards provide for lower lighting levels where there is a lower probability for pedestrian-vehicle conflict.

A bar chart describing the changes in traffic flow for different days of the week sampled from an Arterial roadway sourced from Google Maps averaged across  the range of January 2021 - 2022.
The high traffic periods in this city that require maximum lighting levels represent approximately 10% of dusk-to-dawn hours. Approximately 80% of hours are low-traffic periods. Note that the volumes fluctuate based on the days of the week.

In this last chart, we can see an example of the luminance standards and best-practices from the ANSI/IES RP-8-21 standard, “Lighting Roadway And Parking Facilities”. This standard is used for roadway lighting design in North America[5]. Here, we are looking at the required luminance level for a Local road with an R2 or R3 surface. These are asphalt surfaces commonly used in North America for local roads with low, medium, and high pedestrian sidewalk traffic.

A chart illustrating the roadway luminance levels for a Local R2 and R3 class roadway with high, medium, and low traffic volumes.
An example of the required luminance level for a Local road with an R2 or R3 surface (asphalt surfaces commonly used in North America for local roads).

When we put all this data together, we see that 60% of the city’s roadway lighting can be dimmed 75%-80% of evening hours by as much as 80% of the time compared with peak hour demand. This is the basis for the benefits of dimming street and area lighting.

The key to reducing LED street light electricity use, its GHG footprint, and extending LED lamp life with dimming is a Smart Lighting system.

Smart Street lighting provides lighting designers, engineers, and a city’s operations team with fine control over the city’s lighting. It also provides automation and analytics to management and operations teams to reduce the time and effort required to manage lighting assets.

Not All Street Light Dimming is Equal.

There are several methods of dimming available [6], [7], [8] with Tondo’s Smart Lighting system. Savings factors from several academic studies were used in our business case:

  • Design-Based – based on dimming-enabled photometric design
  • Statistical – based on historical traffic volumes with all days of week equal
  • Statistical Categorization – based on historical traffic volumes, each day of week is unique
  • Sensor Sampled – sensors used to sample traffic volumes in in 15-minute intervals

Lighting designers and engineers can utilize software applications such as DIALux to design street lighting projects according to established standards. However, Smart Lighting controls are required to apply these designs. Lamps and luminaires have different lighting characteristics, must respond to traffic pattern changes, and adjust output according to lamp luminance that degrades over time.

The photometric Design-based dimming is intended to be used together with one of the three  adaptive traffic-based dimming methods: Simple Statistical, Categorized Statistical, or Sensor-Based.

These four methods of Smart Lighting-enabled dimming are compared in the chart below relative to Dusk-to-Dawn operating costs for:

  • Electricity use based on unmetered street light rates [2]
  • Electricity use based on metered street light rates [2]
  • GHG footprint measured in CO2 equivalents and available carbon credits [3],[4]
  • Increased LED lamp lifecycles from dimming [10], [16]
  • Reduced luminaire maintenance truck rolls [11], [12], [13]
A stacked bar chart describing the components of the annual operating costs and benefits of Smart Street and Area Lighting. This includes metered and unmetered electricity costs, lamp lifecycle costs, non-electricity operating and maintenance costs, and GHG footprint costs associated with electricity generation.
Smart Lighting controls can enable as much as a 50% reduction in non-electricity operating expenses and 69% reduction in electricity and GHG footprint.

Let’s zoom in on the value that the three dimming methods plus dimming-enabled photometric design create:

A bar chart describing the annual operating costs of dusk-to-dawn lighting control versus Smart Lighting-enabled dimming controls.
This city can reduce the cost of operating their LED street lights by up to $500,000 per year.

But that’s not all – we still need to look at the non-electrical operating expense of street light maintenance.

How to Reduce Street Light Maintenance Costs with Smart Lighting.

Managing street and area lighting is a lot of work. It is also regulated by safety authorities at the state/provincial and national levels, and subject to regulatory standards.

Maintenance involves both routine and non-routine maintenance activities. These routine activities include:

  • Inspection, testing, cleaning, lubricating, and performing minor repairs as needed
  • Regular visual inspection as part of the replacement of lamps
  • Replacement of luminaires and lamps according to expected lifecycles
  • Testing for voltage and current leakage that can put the public or wildlife at risk

However, there are a number of non-routine activities that include investigating:

  • Wire down
  • Pole down
  • Power supply down
  • Power supply failure
  • Wiring faults
  • Energization of surfaces accessible by the public
  • Vandalism
  • Faulty lamp or luminaire
  • Electricity theft

The transition from older high intensity discharge (HID) lighting to LED lighting addresses the routine maintenance activity of replacing lamps. In addition, Tondo’s Smart Lighting controllers are designed to identify:

  • Faulty luminaires
  • Pole down from tilt
  • Damage to pole or luminaires from weather, vehicle collision, or vandalism
  • Wiring faults at installation time or degradation over time
  • Electricity theft
  • Power quality that can indicate risk to the public

How do we measure these costs?

For the purpose of this business case, we wanted objective third-party data without using our own assumptions. There were a number of studies that suffered from problems in their methodology, and we looked for:

  • Real world measurements
  • Completeness and scope of analysis
  • Published date
  • Detailed cost analysis using real-world city data

The studies [11, 13, 21] show that Smart Lighting technology can save up to 50% in lighting maintenance costs.

Tondo’s Cloud-IQ central management software system collects data from lighting controllers and sensors, and provides actionable analytics and alerts to non-routine conditions to cities.

At this point, the business case becomes obvious for Smart Lighting. This brings us to the question of, What is the value of Smart Lighting as the platform for a Smart City sensor network?

The Street Light-Enabled Smart City Network.

There are many definitions of what a Smart City is, and the definitions continue to evolve. A fair summary of the Smart City definition is a city that:

  • Supports operational efficiencies through technology-based automation
  • Supports economic growth through the provision of technology infrastructure
  • Supports citizen satisfaction with high-availability self-service for city services
  • Supports community development through education, sharing resources
  • Supports citizen engagement through connection with city representatives and voting
  • Decreases the human impact of growing urbanization on our environment and wildlife
  • Improves safety and security
  • Supports equal access to city resources for all citizens

A Smart City uses technologies and innovation to reduce the impact of urban growth on our environment and improve service efficiencies, citizen engagement, community development, education, and economic growth for the benefit of all citizens and businesses.

So how can a Smart Lighting-enabled Smart City Network help?

You Can’t Have a Smart City Without Smart Lighting.

Before a Smart City vision can be realized, cities need a cost-effective, secure, wireless, city-wide communications platform (“network”). This will use a variety of sensors and devices to support Smart City process automation and efficiency.

Street lighting is the natural platform for the Smart City network:

  • Street lighting is everywhere there are infrastructure assets, people, and vehicles
  • Street poles are pre-wired for power
  • Streetlight poles are high up in the air for optimal wireless network position
  • Streetlight poles are convenient locations for a wide range of sensors and devices
  • Streetlight poles are co-located to underground city infrastructure
  • Connection standards already exist to connect network controllers to street lights

Lighting poles represent strategic infrastructure for smart city development, thanks to their capillarity, connectivity and electrification.

The evolution of the street lighting market, Arthur D. Little S.A., October 2019

Tondo’s Smart Lighting creates a secure, open standards-based city-wide network. This enables control over lighting, and also enables cost-effective connectivity for wireless sensors and devices that support Smart City goals.

Smart Cities Need Sensors.

Smart Lighting directly and materially reduces the human impact of growing urbanization on our environment and wildlife:

  • Reduced energy use and GHG footprint
  • Reduced sky-glow that impacts human health, animal and bird migration and reproduction
  • Improved aesthetic and scientific research value of a dark night-time sky

Operational efficiencies, economic growth, improved safety and security, and citizen self-service delivery for Smart Cities depends on better information – faster. Sensors help cities gather data to more effectively manage a range of services including:

  • Transportation
  • Flood control
  • Water quality
  • Gas or fluid leak detection
  • Sanitation services
  • Parking occupancy
  • City asset theft or vandalism
  • Air quality
  • Public safety and first-responder resource management
  • Infrastructure health and degradation

Most sensors today require proprietary technologies and multiple stand-alone platforms for managing devices and data. These approaches present two major risks for cities:

  1. An economic hold-up problem locking cities into purchasing devices through that vendor. There are few* examples of vendors who have decreased their SaaS prices as they have gotten larger and increased their economies of scale.
  2. A technical hold-up problem locking cities into purchasing devices that are compatible with a proprietary technology platform. There are few* examples of proprietary technologies that have survived after open standards have been established.

* I will argue “none” in the 40 years I have been working in the technology sector.

With Tondo’s open, standards-based network and management platform, the city is not locked in to a specific vendor’s products – including Tondo’s.

Controlling Smart City Sensor Costs.

Let’s look at a manhole cover use-case as an example. Why manhole covers instead of water quality, gas leak detection, storm drain levels, or many other use-cases? This article in the New York Times caught my eye recently: Where have all the manhole covers gone? .

Manhole sensors cost hundreds or in some cases, thousands of dollars, with monitoring fees charged monthly. When the number of sensors is relatively low, the operational costs of these sensors are not always noticeable. SaaS or monitoring costs from $10 to $50 or more per sensor per month charged by some vendors make city-scale projects uneconomical.

The city that was used for street and lighting data in this article [1] has 7,303 standard light pole street lights, 2,537 city street blocks, and 269 crosswalk-marked intersections. The city also has 4,060 sewer manholes and 3,444 storm drain manholes for a total of 7,504 manholes – more manholes than street lights.

The value of a Tondo Smart Lighting-enabled Smart City network for sensor and device connectivity is based on the costs of the network offset by the operating cost savings from street lighting.

A bar chart comparing the 10-year total costs of deploying city-wide sensors with and without a Smart-Lighting enabled Smart City network.
Using an assumption of $10.00 per month in SaaS costs per sensor for a competitor’s proprietary or independent sensor network, this chart shows the 10-year net cost difference vs a Tondo Smart Lighting-enabled sensor solution.

Tondo’s Smart Lighting creates a net cash-flow positive Smart City sensor platform that prevents costs from spiralling out of control.

Tondo’s Smart Lighting creates a secure city-wide network that not only enables control over lighting, but also enables connectivity for wireless sensors and other connected devices that enable Smart City applications.

A bar chart describing the cash flows and break-even of a Smart Lighting and Smart City network project with three sensors deployed per city block.
The break-even for Smart Lighting only is 4.5 years, and this drops to 4 years with a three sensor-per-city-block project – and avoids over $17m in future costs.

This cash-flow positive Tondo’s Smart Lighting solution for 7,303 luminaires on 2,537 city blocks offsets the cost of the Smart City network, showing a project IRR of 13.8% without including savings from sensor deployment, and 52.6% when including sensors in the analysis.  The break-even for Smart Lighting only is 4.5 years, and this drops to 4 years with a three sensor-per-city-block project – and avoids over $17m in future costs.

The Business Case for Smart Lighting as the Smart City Network.

This is a lot of information to take in. The first barrier to reducing energy costs, operating costs, and the GHG footprint of our energy use is reliable information.

The key takeaways from this case are:

  • Moving lighting from unmetered to metered rates and cut their energy costs by 50% or more[Jump to Section]
  • Tondo’s Smart Lighting enables cities to deliver standards-based lighting according to demand, for a savings of 70%[Jump to Section]
  • Network-controlled Smart Lighting has been shown to cut non-electricity operating costs of managing street lighting by 50%. [Jump to Section]
  • The reduction in electricity use from adaptive dimming also extends the life of LED lamps by 60%-70%[Jump to Section]
  • To cost-effectively enable a Smart City strategy, cities require secure, standards-based wireless networks for sensors and devices to operate on.
  • Tondo solutions provide a secure city-wide wireless network platform that can reduce the capital and operating cost of sensors by 60% or more. [Jump to Section]
  • A Tondo Smart Lighting project provides a positive cash flow with a 13.8%+ internal rate of return (IRR) and a 4 year project break-even.[Jump to Section]
  • A Tondo Smart Lighting sensor network can triple project IRR and increase the annual benefit by 2.7x [Jump to Section]
  • A Tondo Smart Lighting project provides 85% of the benefits versus LED retrofit, and a Smart City sensor network project can provide 280% of LED retrofit benefits. [Jump to Section]

If you have questions or comments for us on this article, please contact us through the Contact Us form on our website at www.tondo-iot.com.

A Tondo Smart Lighting-enabled Smart City sensor network will provide municipalities with significant long-term value, and establish their platform for Smart City enablement.

Methodology, Sensitivities, and Assumptions.

This article is based on a comprehensive economic model developed internally at Tondo. It uses a city’s ArcGIS data, Google Maps data, and established street lighting standards to accurately assess the costs and benefits of Tondo’s Smart Lighting and Smart City network projects. However, there are a number of assumptions and input values that may cause significant changes to these predicted values.

Sensitivities for this business case include but are not limited to:

  • Changes to ANSI/IES RP-8-21 roadway lighting standards [1]
  • Cost of electricity [2]
  • Composition of lighting assets and corresponding input wattage [1]
  • CO2 footprint of electricity [3]
  • Cost of CO2 carbon credits if available [4]
  • Additional project management, provisioning, and configuration costs
  • Cost of third-party software integration
  • Any custom software or hardware development required in a project
  • Capital cost of sensors [14]
  • Number of luminaires [1]
  • Crosswalk-based intersections [1]
  • Number of streets for each road surface and classification [1]
  • Currency conversion rates between Canadian and U.S. dollars, if applicable
  • Assumptions for sensor ratio to number of city blocks used in the case [1]
  • SaaS cost assumptions for proprietary sensor solutions used in the case [14]
  • Non-standard lighting levels required by city practices
  • Assumption that all existing city luminaires support dimming control and industry-standard connections

Although it is not practical to cover all aspects of our business case model in this article, our internal model does allow for us to tailor these and other assumptions for a specific use-case.

If you are interested in having your city’s data used to produce a similar cost-benefit analysis of your own Smart Lighting and Smart City Network initiative, please contact us through this website and we would be happy to help.

Citations and Sources.

[1] Data sample used for composition of Streets, Intersections, Manholes, Lamps, and Luminaires

[2] BC Hydro Street and Area Lighting Rate Schedule 1702, Customer-owned luminaires, effective March 8, 2022

[3] Greenhouse Gas / CO2e footprint per kWh, Government of British Columbia, January 2023

[4] Greenhouse Gas / CO2e costs, Government of British Columbia, January 2023

[5] Standards used to calculate dimming values for Streets, Intersections, Vehicle and Pedestrian Traffic ANSI/IES RP-8-21

[6]  Enhancing Energy Efficiency of Adaptive Lighting Control, Adam Sedziwy, Leszek Kotulski, and Artur Basiura; N.T. Nguyen et al. (Eds.): ACIIDS 2017

[7] Economic Impact of Intelligent Dynamic Control in Urban Outdoor Lighting, Igor Wojnicki, Sebastian Ernst and Leszek Kotulski, 25 April 2016

[8] Roadway Lighting Retrofit: Environmental and Economic Impact of Greenhouse Gases Footprint Reduction, Sedziwy, A.; Kotulski, L.; Basiura, A.; 29 October 2018

[9] Traffic volume classifications re: ANSI/IES RP-8-21:  District of North VancouverRoadway Lighting Retrofit: Environmental and Economic Impact of Greenhouse Gases Footprint Reduction

[10] Effect of adaptive control on the LED street luminaire lifetime and on the lifecycle costs of a lighting installation, J Askola MSc., P Karha DSc, H Baumgartner DSc, S Porrasmaa BSc and E Ikonen DSc, 16 March 2021

[11] A model for the assessment of energy‑efficient smart street lighting—a case study, Shekar Viswanathan, Shamsullah Momand, Mohibullah Fruten, Alejandro Alcantar, 2021

[12] BC Hydro street light service rates

[13] Technical and economic analysis of a Smart Public Lighting model, Bucci, F.; Annunziato, M.; Moretti, F.; EPJ Web of Conferences 33, 05010 (2012)

[14] Cost of manhole cover sensors: City of Torrance, CA RFP

[15] Effects of high traffic flow on dimmable hours, data sampled by author from Google Maps 2022

[16] Impact of luminaire models on optical efficiency/lumens per watt: AcuityBrands ATB0 luminaire technical specifications, 2022

[17] The Study of Lighting Quality of LED and HPS Luminaires Based on Various Road Surface Properties, Suntiti Yoomak , and Atthapol Ngaopitakkul, 2018

[18] Maryland Energy Administration, Municipal Street Light Program, Summer 2021

[19] Sunrise calculation, Wikipedia, 2023

[20] ANSI C136.50 Energy Measurement For A Network Lighting Control (NLC) Device With A Locking-Type Receptacle, and C136.52 Metering Performance Requirements for LED Drivers

[20] The Design, Installation, Operation, and Maintenance of Street Lighting Assets, Electrical Safety Authority, May 2015

[21] Gagliardi G, Lupia M, Cario G, Tedesco F, Cicchello Gaccio F, Lo Scudo F, Casavola A. Advanced Adaptive Street Lighting Systems for Smart Cities. Smart Cities. 2020


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A bar chart describing the difference in the 10 year cost of operating sensors with and without a Smart Lighting-enabled Smart City network.

Tondo Smart Lighting also creates an open standards-based Smart City network for connecting sensors and other wireless and wired devices to Tondo's Cloud-IQ management platform.

This can reduce sensor and device deployment costs by 80% or more versus proprietary networks or individual cellular connections, with a 2.7x or greater benefit versus your LED retrofit project, and 3.5x over Smart Lighting alone.

A stacked bar chart that details the operating costs of street and area lighting, and the savings available with Smart Street and Area Lighting controls.

Read more about the Business Case for Smart Lighting on this link.

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CAT-M/LTE-M and NB-IoT are similar but have differences that may make one suitable over another, or simply selected based on the support for one or the other that is available in your area.

NB-IoT uses a narrow bandwidth of 200 kHz, where CAT-M uses 1.4 MHz. The maximum data rate for NB-IoT is ~ 250 kb per second, with CAT-M1 reaching ~ 1 Mbps. CAT-M is marginally less energy efficient than NB-IoT. Although NB-IoT has a lower speed, both NB-IoT and CAT-M are suitable for sensor communications since sensors typically do not require much bandwidth.

Both NB-IoT and CAT-M1 are supported under the 5G technology specifications and therefore are ideal for selecting as a standard for sensor communications.


CAT-M wireless (aka LTE-M) is a low-power wide area network (LPWAN) cellular data transmission standard that operates over the data and physical layer. CAT-M was designed for IoT projects, with an average upload speed between 200 kbps and 400 kbps.

Eddystone is an open-source Bluetooth advertising protocol originally designed by Google. It can be used by mobile device applications to deliver improved proximity-based experiences that include applications such as Google Maps.

These packets can be discovered with any Bluetooth LE APIs such as Core Bluetooth on iOS, or android.bluetooth.le on Android. You can also use them with Google’s Nearby Messages API, which can be integrated into an iOS or Android app, and receive “messages” in those apps when a person enters or exits a range of beacons.

You can read more about it on github.com/google/eddystone.

Source: US Department of Energy 2015 U.S. Lighting Market Characterization, issued November 2018

Tondo's 2022 estimate was calculated for each lighting category by applying market growth factors for each lighting category between 2015 and 2021 based on U.S. Census data to the DOE dataset.

The original Excel data set can be downloaded here.

A RESTful API is an architectural style for an application program interface (API) that uses HTTP requests to access and use data.

The API spells out the proper way for a developer to write a program requesting services from an operating system or other application.

You can read more from the source of this definition at TechTarget here.

A DIN rail is a metal rail of a standard type widely used for mounting circuit breakers and industrial control equipment inside equipment racks.

IP stands for "ingress protection". For IP67, this means:

"6" describes protection of solid particles: No ingress of dust; complete protection against contact (dust-tight). A vacuum must be applied. Test duration of up to 8 hours based on airflow.

"7" describes the protection from water: Ingress of water in harmful quantity shall not be possible when the enclosure is immersed in water under defined conditions of pressure and time (up to 1 meter (3 ft 3 in) of submersion). Test duration: 30 minutes.

Modbus is a data communications protocol originally published in 1979. Modbus has become a de facto standard communication protocol and is now a commonly available means of connecting and communicating with industrial electronic devices.

Read more about MODBUS here.

RS-485, also known as TIA-485(-A) or EIA-485, is a serial communications standard.

Electrical signalling is balanced, and multipoint systems are supported. Digital communications networks implementing the standard can be used effectively over long distances and in electrically noisy environments.

This table describes the differences between 3G, 4G, and 5G cellular communications standards.

4G devices will work on 4G LTE networks and the earlier cellular technologies, including 3G, EGPRS, and 2G.

Smart city sensors require very little bandwidth, and 3G EGPRS and 4G LTE can easily support the required data rates.

5G networks are relatively new, and most 5G deployments use a combination of 4G and 5G networks.


A diagram describing the DALI smart lighting control system

DALI-2 refers to the latest version of the DALI protocol. While DALI version 1 only included control gear, DALI-2 includes control devices such as application controllers and input devices (e.g. sensors), as well as bus power supplies.

Read more at the DALI Alliance website: Compare DALI v1 vs DALI v2

Tondo Mobile Field App Dashboard view screenshot

Zhaga Book 18 describes a smart interface between outdoor luminaires and sensing/ communication nodes.

Zhaga Book 18 allows any certified node to operate with any certified luminaire. Certified luminaires and sensing / communication modules are available from multiple suppliers, establishing an ecosystem of compatible products.

Tondo Mobile Field App Dashboard view screenshot

The NEMA ANSI C137.4-2021 builds on the NEMA C137.41 7-pin connector standard and the DALI communication protocol. It has additional characteristics and features that align very closely with the D4i family of specifications from the DALI Alliance.

D4i and ANSI C137.4-2021 specify the digital communication between luminaires and devices including sensors and network lighting controllers. The expanded ANSI C137.4-2021 now includes energy reporting data and diagnostics and maintenance data.

Tondo Mobile Field App Dashboard view screenshot

The NEMA ANSI C137.10 standard specifies roadway and area lighting equipment connector compatibility. The 3-pin standard does not provide for dimming control, but provides for on/off operation. The later standard C137.41 adds dimming control (5- and 7-pin connectors) and sensor control (7-pin connectors). The newer C137.4-2021 standard provides enhanced functionality and compatibility with the DALI D4i lighting and sensor control standard.

Tondo Mobile Field App Dashboard view screenshot

The NEMA ANSI C137.41 standard specifies covers roadway and area lighting equipment connection interoperability. The 7-pin receptacle provides for dimming control and sensor communications.

Tondo Mobile Field App Dashboard view screenshot

The NEMA ANSI C137.41 5-pin connector variant adds support for dimming control, but does not include sensor communications support which is supported by the 7-pin connector.

DALI, or Digital Addressable Lighting Interface, is a dedicated protocol for digital lighting control that enables the easy installation of robust, scalable and flexible lighting networks.

Wiring is relatively simple; DALI power and data is carried by the same pair of wires, without the need for a separate bus cable.

Read more at the DALI Alliance website: Introduction to DALI

The TALQ Consortium has established a globally accepted standard for management software interfaces to configure, command, control and monitor heterogeneous outdoor device networks (ODN) including smart street lighting.

This way interoperability between Central Management Software (CMS) and Outdoor Device Networks (ODN, so called ‘gateways’) for smart city applications from different vendors is enabled, such that a single CMS can control different ODNs in different parts of a city or region.

Read more at the TALQ website

Tondo Mobile Field App Dashboard view screenshot

D4i is the DALI standard for intelligent, IoT-ready luminaires.

By taking care of control and power requirements, D4i makes it much easier to mount sensors and communication devices on luminaires. In addition, intelligent D4i LED drivers inside the luminaire have the capability to store and report a wide range of luminaire, energy and diagnostics data in a standardized format.

Infographic of Bluetooth Technology Global Standards

Highly reliable hardware, firmware, and software components that perform specific, critical security functions. Because roots of trust are inherently trusted, they must be secure by design. Roots of trust provide a firm foundation from which to build security and trust.

Read more at the National Institute of Standards and Technology: Roots of Trust

The 0.1, 0.2, and 0.5 accuracy class electricity meters established within ANSI C12.20-2015 are accurate to within +/-0.1%, +/-0.2%, and +/-0.5% of true value at a full load.

Read more at the ANSI Blog: ANSI C12.20-2015 – Electricity Meters – 0.1, 0.2, and 0.5 Accuracy Classes.

Source: US Department of Energy 2015 U.S. Lighting Market Characterization, issued November 2018

The full Excel data set that accompanies this report can be downloaded here.

Tondo's controllers utilize a chipset containing the ARM Cryptocell 300 cryptographic accelerator chip with hardware-protected vault and Root of Trust security. Read more about the ARM 300 family here: ARM Cryptocell 300 Family Overview

The world would collectively achieve 10,546 TWh of energy savings by 2030 [with energy efficient lighting], a sum comparable to over 40% of the world electricity generation in 2011. Saving this amount of energy would prevent the emissions of 5,400 Mt CO2, a figure equivalent
to over 15% of the global emissions in 2011.

Source: United Nations Environment Programme (2014). Green Paper - Policy Options to Accelerate the Global Transition to Advanced Lighting.