When we talk about “Dark Spots” in a city, most people imagine poorly lit streets, broken lamps, or a maintenance issue for the public works department.

But in the context of a Smart City, Dark Spots are a strategic metric closely tied to at least three major dimensions:

  • Crime and incident risk in specific locations
  • How safe citizens feel when they move around the city
  • Long-term investment decisions in Smart Poles, CCTV, and smart streetlighting

In other words, “every Dark Spot is both a risk point and a future investment decision point for the city.”

1. Why “counting Dark Spots” is not enough

Many cities have already started counting how many Dark Spots they have. But if we only look at the number, we still don’t have answers to questions like:

  • Which Dark Spots are more dangerous than others?
  • Which locations affect a large number of people even if incidents are rare?
  • Which areas should receive priority investment in smart lighting or CCTV?

That is why cities need to move beyond simple counting and start designing Dark Spot as a real decision-making metric.

2. Treat Dark Spots as a metric, not just an electrical issue

Dark Spots can be turned into a city-level metric in at least three main dimensions:

2.1 Crime & incident dimension

Some key questions a city should ask:

  • Which Dark Spots are close to locations with frequent theft, assault, or other incidents?
  • Which Dark Spots are on routes used by students, night-shift workers, or the elderly?
  • Are there pedestrian or bicycle routes with a continuous stretch of poorly lit areas?

The city can create a concept like “crime-weighted Dark Spot”, where each Dark Spot is weighted by crime statistics and complaint data. This helps surface the truly high-risk Dark Spots, not just the ones with broken lamps.

2.2 Citizen perception & confidence dimension

Some areas may not have frequent incidents, but people still feel unsafe, for example:

  • Dark corners of public parks where people avoid jogging at night
  • Pathways along canals that have a “bad reputation” or past incidents
  • Neighborhoods where residents leave house lights on because they don’t trust street lighting

Cities can collect data through multiple channels, such as:

  • Online surveys or QR codes placed in public areas
  • Mobile apps or hotlines for citizen complaints
  • Behavioural data, such as parks that become empty after 8 p.m.

This can be transformed into a “Citizen Confidence Score” for each district, highlighting areas that are “dark in people’s minds” even if lamps are physically present.

2.3 Investment & infrastructure dimension

Decisions to invest in Smart Poles, CCTV, or smart lighting should go beyond the argument that “many lamps are broken here.” Additional questions could include:

  • Is this area a key economic zone or a dense residential district?
  • Is there a plan to connect this area with broader Smart City or IoT infrastructure?
  • What risks can be mitigated if we invest in Smart Poles/CCTV here?

Once Dark Spot data is analysed alongside urban development and zoning plans, it becomes a critical layer in the city’s Master Plan and 3–5 year infrastructure investment roadmap.

3. From dark corners on the street to a Command Center dashboard

When Dark Spots are treated as a metric, they deserve a place on the city’s central dashboard, just like traffic or air-quality maps. A Dark Spot dashboard could show:

3.1 Dark Spot heatmap

  • Risk levels: normal / at-risk / high-risk
  • Continuous Dark Spot segments along important pedestrian routes

3.2 Data layers

  • Current locations of CCTV, Smart Poles, and streetlights
  • Crime and incident statistics by area
  • Critical locations such as schools, markets, hospitals, and parks

3.3 City-level KPIs

  • Share of urban area classified as Dark Spot (%)
  • Number of high-risk Dark Spots resolved per month/quarter
  • Trend in average citizen safety perception scores across districts

4. Connecting Dark Spots to Smart Pole / CCTV / Lighting investment

Once Dark Spots are monitored systematically, the metric naturally feeds into decisions on where and how to invest.

4.1 Selecting Smart Pole / CCTV locations

Instead of relying only on “gut feeling” or isolated complaints, cities can rank locations by:

  • Dark Spots with high crime or incident correlation
  • Areas where people feel unsafe but that have strong public-use potential
  • Strategic connectors such as paths between transit hubs, parks, and public facilities

4.2 Feeding into TOR and Smart City roadmap

Dark Spot metrics can be translated into TOR requirements, such as:

  • Smart Pole / CCTV solutions must integrate with the city’s Dark Spot data layer
  • Dashboards must show lighting and CCTV status in the context of safety and risk
  • Systems must support export and analysis of historical Dark Spot trends over 3–5 years

5. How cities can get started: a “Pilot + Data-first” approach

For cities that want to begin without committing to a large project immediately, a pilot-plus-data approach can work well:

  1. Map initial Dark Spots
    Use field surveys, citizen complaints, or even crowdsourced photos.
  2. Define what “Dark Spot” means
    Involve both technical and safety teams to set a clear definition (e.g., lux levels below standard, blocked line-of-sight, no CCTV coverage).
  3. Bring the data into a central dashboard
    Visualise Dark Spots as a layer with severity and context.
  4. Link with crime, emergency, and complaint data
    Identify Dark Spots with the highest combined risk.
  5. Design short-, medium-, and long-term actions
    Immediate repairs, temporary lighting, Smart Pole/CCTV deployment, and urban design improvements.
  6. Define measurable KPIs
    For example: “Reduce high-risk Dark Spots by 50% in 12 months,” or “Increase average citizen safety perception in District X from 3.1 to 4.0.”

6. Conclusion: a small metric with a big impact on the city

Dark Spots may look like a minor issue – a broken lamp or a dark alley – but through the Smart City lens they become a metric connecting:

  • Protection of life and property for citizens
  • Citizens’ trust and comfort in using public space
  • Long-term infrastructure investment and budget allocation

A city that “understands its own Dark Spots” is not a city with many broken lights. It is a city that turns every Dark Spot into data, and uses that data to design a brighter, safer, and more inclusive future.