analysis
Market Analysis
Our business, Lumino.net is attempting to reach the ITM (Intelligent traffic management) market, currently valued at 9.22 billion dollars, with our concept, AITOS (AI-based Intelligent Traffic Optimization System). AITOS will use novel technologies to revolutionize the ITM sector.
AITOS will be designed to optimize current traffic systems, for most current systems prove to be highly inefficient, causing several consequences. AITOS functions using 2 main components, TDMs (Traffic Data Module) and AINS (AI-based Intelligent Navigation System) (check technical concept for more info).
(Refer to funding for details on phases/rollout.)
Our target market with AITOS is consumers/general public, AV manufacturers, and governments. During phase 1 (3 cities of Canada) and 2 (all of Canada), we will be exclusively working in Canada. For TDMs, we intend to pursue a contract with the Canadian government, charging a fixed fee for each unit of TDMs utilized. Moreover, the sale of AINS will be divided into 2 parts, the mobile and AV version of AINS. The mobile version of AINS will be available publicly to download on all mobile devices. With this app, our target demographic will be Canadians aged 16 - 65 that are able to drive. Most of our target demographic will be interested in our concept, as traffic systems are very inefficient in Canada. Our AV version of AINS will be licensed to small AV manufacturers such as Motional and Zoox. We will charge them a royalty fee for each installation of AINS on AVs. We will have no real competitors during this stage, other than global navigation businesses, as there are no ITM businesses in Canada. These two phases will allow AITOS to be well-known within the ITM market, allowing for further expansion.
During phase 3 (all of North America) and 4 (global), we intend to follow a similar plan as phase 1 and 2. We hope to pursue contracts with all governments in the world, for the use of TDMs. The fixed fee will remain the same. We also hope to profit more from AINS. The target audience for our mobile version of AINS will shift to everyone, aged 16-65, that is able to drive. Similarly to Canada, as many countries are in dire need of efficient traffic, AITOS will be very appealing to our target demographic. With this shift, we also intend to charge fees for each installation of our AINS app. Next, with our AV version of AINS, we intend to license with a multitude of AV manufacturers. However, our main target will be big AV manufacturers such as Tesla, Waymo, Cruise, etc, as they will contribute the most to upcoming company growth. During these phases, we will have several competitors such as Valerann, Miovision, Waze, and Google maps.
Competitive Analysis
Lumino.net has several competitors in the global ITM (Intelligent Traffic Management) market. Businesses such as Valerann and Miovison aim to reduce traffic congestion by monitoring traffic states and offering traffic management insight to other companies. Their target market is other businesses that require their accumulated data. Google maps and Waze aim to reduce traffic congestion by preventing traffic accumulation by leading people away from congested areas with their smart navigation software.
Valerann and Miovision accumulate and provide crucial traffic data to other businesses. Although they have found success using this concept, they were not able to achieve significant or rapid growth due to their target market. They only target other businesses and charge a fee for the use of their app and data. Their app is not available for public use. For this reason, at first, when their businesses were not well known, it was very challenging to see growth.
Google maps and Waze accumulate GPS data necessary for their smart navigation application. Their app is free, and they mainly profit through advertisements. They advertise other businesses and charge a fee per ad. This method of income proves to be highly unreliable. These apps are only able to sustain themselves, for they are already a massively successful business. Their user base is immense, with over 100 million downloads. Therefore, this method will prove to be highly unreliable for small to medium-sized businesses that will have substantially fewer users.
AITOS will be better than all competing concepts due to its unique services, quality, and smart marketing plans. From Valerann and Miovision’s marketing plans, our company realized that multiple and large target markets are often necessary for a stable business. For this reason, we intend to target governments, AV manufacturers, and the public as our main target/consumers. Connecting with the public will allow us to see rapid growth during the initial stages of our business, something that was absent for Valerann and Miovision. Furthermore, we will deal with competitors for AINS, our navigation application, such as google maps and Waze by offering higher quality software for a small price. By using a similar concept to Valerann and Miovision, AIT, our product is better and more efficient than those already in existence, as the most common type of traffic lights have time cycles that do not have any variables that change the time on a certain colour.
For example, some types of traffic lights use pressure plates underneath the road, which can detect cars when they are on the pressure plate and changes the time on a certain colour, depending on how many cars are on them. Although, it is very common that these pressure plates sometimes do not detect the cars on top, which will make fully automated cars in the future much more dangerous and risky, and would not guarantee safety when driving fully automated. So a solution such as using signals for traffic lights would be a much more ideal and secure method for traffic light detection. Using signals is great because of that, but also because of the rapid data-sending speed, which can reduce the number of accidents where every millisecond is crucial.
Tesla and other automated car-making companies use forward-facing cameras to detect traffic lights and to identify the colour of the traffic light, which would again, not guarantee safety as there are variables such as the weather, that can hugely affect the performance of the system. For example, the camera can be blocked by snow, ice, heavy rain, etc. So again, using signals is the solution here because there are very few variables that are also very unlikely to happen that can change the signal’s performance. Our product is also going to have a LiDar system in the poles so that we can organize the cars by shooting out infrared lasers to detect the size, shape, and position of the vehicles on the road.
With the help of the signals and the LiDar system, we can collect data and analyze traffic patterns over time, meaning that we can easily predict traffic and determine the fastest routes for cars by using machine learning. It is a very similar concept to Google’s traffic-prediction system, except that now every individual car can now be detected and will give much more accurate data, which results in a more accurate traffic prediction without the need for complex satellites and agencies such as OC Transpo, Dufferin construction, and NJMC. OC Transpo focuses on public transport and tries to dissuade people from using private automotive vehicles. Although this is very environmentally friendly, it fails to gain popularity, rendering its effects minimal. Dufferin construction tries to address this problem by working on highway expansion. Studies have shown that increasing the tolerance of the highway will also augment the number of people using the highway.
(insert linear graph of tolerance and uses of highway) Not only is this solution very costly, it is also temporary, as it fails to address the root cause of congestion. NJMC approached this problem with a more novel perspective, by enabling more efficient traffic flow. MASSTR (Meadowlands Adaptive Signal System for Traffic Reduction) uses cameras to detect current traffic flow and uses an algorithm to find the most effective way to change traffic lights to find the most efficiently way.
Reference
https://blog.google/products/maps/google-maps-101-how-ai-helps-predict-traffic-and-determine-routes/
Google maps/navigation system company: does not use many satellites, AI technology
Meadowlands Adaptive Signal System for Traffic Reduction
https://en.wikipedia.org/wiki/Meadowlands_Adaptive_Signal_System_for_Traffic_Reduction
Dufferin construction
https://www.dufferinconstruction.com/expertise/roadways/
https://tracxn.com/d/trending-themes/Startups-in-Smart-Traffic-Management
OC Transpo
https://www.valerann.com/solutions
Although this company successfully manages data, it has no actual control over traffic.
Google maps:
Although this company successfully creates an effective way of travel, it is overly dependant on its users to manage traffic.
cost
Net development expenses
The expenses for creating AITOS will mainly come from manufacturing TDMs and creating AINS. TDMs consists of 6 primary parts: Stainless steel case, Arduino wifi motherboard, breadboard, LiDAR camera, Solar panel, and battery. Upon arranging values, we found that the Stainless steel case will cost approximately $27, the Arduino wifi motherboard will cost $43, the breadboard will cost $10, the LiDAR camera will cost $199, the solar panel will cost $30, and the battery will cost $22.50. Thus, including the cost of each component and assembling fees, we predict that manufacturing one unit of TDM will cost $350. We will weld each unit of TDMs to traffic light poles. On average, we expect the welding fee to be $15 for each TDM, making the net cost $365. We also expect a fee of $10000 for our initial testing costs.
Although it is a little more difficult to estimate the price for developing AINS (AI base intelligent Navigation System), we expect that it will cost somewhere in the $300000 to $400000 range. Most applications range from $100000 to $700000, depending on their complexity. As we are creating an application using novel ideas and technologies (AI, AVs), we expect our application to be moderately complex. Thus, considering labour fees and costs for developing the app, we expect about $300000 to $ 400000 in expenses. We hope to make a one-year contract with 5 software engineers with much experience for a salary of $70k to $80k. We hope to finish developing AINS within a year (specifications for developing AINS could change as other variables are introduced).
Net implementation expenses
AITOS will be implemented in 4 phases (check the market entry in funding).
During phase 1, we will implement AITOS in cities such as Ottawa, Toronto, and Montreal. TDMs will be placed beside each traffic light. There are approximately 6200 traffic lights in these regions. Thus, we will need to manufacture 6200 TDMs, which will cost $2.17 million. We will also need 3 servers, each costing $10000. For AINS, to ensure proper functionality, we will need at least 80% of the population that is able to drive to install our application. The total population that is able to drive of Ottawa, Toronto, and Montreal is approximately 1.6 million, thus we will need at least 1.2 million installations during this phase. We will mainly be advertising to the Canadian public using social media and social network platforms such as Instagram, Twitter, Facebook, Youtube, etc. We will set aside a budget of $15000 for advertisements.
During phase 2, we will implement AITOS in all of Canada. Estimates show that there are approximately 28000 traffic lights in Canada. 28000 TDMs will cost $10.22 million. During this phase, we will need up to 250 servers to cover the entirety of Canada. This will cost $2.5 million. To have over 80% of the population install AINS in all of Canada, we hope to advertise with a budget of $30000.
During phase 3, to cover North America, we will need more than $110 million to manufacture over 300000 TDMs, over $50 million for servers, and $50000 for advertisements.
We have not considered the cost of global expansion, for there are too many unknown variables.
Profits/revenue
We intend to sell each TDM for $500 to the government. Thus, the margin per unit will be $135.
We intend to make AINS free for phase 1 and 2, but we will charge a $5 installation fee starting from phase 3.
For the AV version of AINS that will be licensed to AV manufacturers during phase 2, we will charge a $25 royalty fee.
By phase 1, we expect to make a profit of $272000. (6200 traffic lights x margin per unit - (ad + testing + server + software development)
By phase 2, we expect to make a profit of $2.5 million. (28000 traffic lights x margin per unit + 50000 AVs x royalty - (ad + server))
By phase 3, we expect to make a profit of $267 million. (300000 traffic lights x margin per unit + 1.4 mil AVs x royalty + #drivers in North America x installation - (ad + server) )
Extra profits (as needed)
During Phase 1 and 2, for more profit, we will also try to explore the possibility of selling AINS to other car manufacturers (non-AV). Furthermore, we will also advertise other apps on AINS, charging a cost per click, to help secure more profit.
All dollar units without specifications are in CAD.
Funding Sources
As it was covered briefly in the cost section, our business will follow a detailed plan as we enter the market.
First, during the pre-developmental stages of AITOS, we will advertise AINS to gain public attention. Then, as we manufacture TDMs, we hope to pursue government contracts in a few major regions in Canada such as Ottawa, Toronto, and Montreal (Phase 1). Our contract will charge the government a fixed fee for each unit of TDMs sold. As the TDMs are being installed in major cities, we will release our mobile-only version of AINS. AINS will be targeted to the 16-65 age demographic, that is able to independently use public/private transport methods. We have targeted this age demographic, because it covers the majority of the current population, and because they will be the ones noticing the differences made by AITOS. This will allow AITOS to gain rapid public attention. After a few weeks or months, we will expand toward the entirety of Canada (Phase 2). We will pursue a government contract with all cities in Canada, with the same terms. We will also release our AV version of AINS at this point in time. We will license AINS with small AV manufacturers, such as Motional and Zoox, to help us prepare for expansion towards all of North America. We will charge them a royalty fee for each installation. To help AINS gain more attention, we will extensively advertise through social media platforms that are widely used by our target demographic. This will make our advertisements very effective. As we see success in Canada, we hope to expand to other countries in North America (Phase 3). We hope to obtain government contracts with the U.S. and other countries for the use of TDMs. We will also license AINS with bigger AV manufacturers such as Tesla, Waymo, and Cruise. This will help us prepare for global expansion, as these manufacturers are widely known across the world. Moreover, We also plan to charge fees for the installation of our mobile AINS app to gain more profit. Once we have become well-known in the industry and have implemented AITOS in all of North America, we hope to expand globally (Phase 4), by implementing our concept in different parts of the world.
We intend to obtain pre-seed funding through government loans and personal investments. We intend to apply for the futurpreneur Canada start-up program, which is very easy to acquire due to its low requirements. This will make our business eligible for a loan of up to $20000 (all dollar units without specification are in CAD), which we can then appeal for a loan of up to $60000. This fund will be used to get our first operations functional and will come before phase 1.
We intend to obtain seed funding, necessary for our expenses in phase 1 through Angel Investors, and a grant of up to $ 4 million per year. We expect to successfully acquire these funds, for we have virtually no competitors. There are no businesses similar to ours in the ITM sector of Canada. These funds will be used to cover the $1.292 million in developmental costs (check costs section). These funds will help AITOS enter phase 1.
As we transition to Phase 2, we will be implementing AITOS in all of Canada. We expect to spend approximately $12.7 million dollars. To cover these expenses, we hope to obtain series-A funding through venture capital firms such as BDC capital and Qualcomm ventures. BDC Capital is a large Canadian venture capital firm that focuses on the technology sector. As we have no competitors in the ITM sector of Canada, we expect to interest and gain funds from BDC Capital. Moreover, recently, Qualcomm ventures have shown interest in businesses concerning AVs, and AIs. As this venture capital firm is located in America, we expect to compete with a few other businesses in the ITM sector. However, we hope to secure the funds by providing innovative services and applications that our competitors do not.
From then onwards, we will acquire funds from big Venture Capital Firms. We hope to continue working with BDC Capital and work with new firms such as Greycroft and Canaan partners that are interested in innovative and visionary technological businesses.