An Introduction to Location Intelligence and Artificial Intelligence
How location intelligence combined with artificial intelligence has and will continue to have a massive impact on our world.
In real estate, there is a common saying: location, location, location. The location of a house can drastically increase or reduce the property’s price. This is simlar to humans — kind of.
Where a person has been, currently is, or will go can be very beneficial to first responders, insurance companies, and more. This information is called location intelligence (LI). In order to maximize the potential of location intelligence, it is imperative to process and analyze location data efficiently. That is where artificial intelligence (AI) comes in handy. So when we combine both technologies togeather we can make better decisions for our business and societies.
Before we get into the nitty-gritty of this topic, here is an outline of what I will be talking about in this article:
The Case for Location Intelligence and Artificial Intelligence
How to Collect & Process the Data
Ethics (coming soon)
Examples of LI and AI
Why should we use location intelligence and artificial intelligence, and why should you care about this article? Well, you should care because it can disrupt many industries and solve many problems. Here are 3 case studies on how LI and AI have changed the way we live.
Case Study 1: Car Congestion In India
According to the Air Quality Index (AQI), air pollution in Delhi is so harmful it is like smoking 50 cigarettes a day. This pollution is mainly caused by cars. And, with nearly 12 million vehicles on the road, about 40-60% of that time is spent in traffic. So, we are producing hundreds of metric tons of greenhouse gases doing nothing. Additionally, not only is congestion costing lives but it is also costing real money — nearly $22 billion! So, a company called Y&R decided to tackle the problem of traffic in India using LI and AI.
In India, cows are very sacred animals. This means traffic could be held up because of cows crowding the roads.
In order to solve air pollution and traffic congestion, Y&R decided to place trackers on the cows by recycling old cell phones to admit a cellular signal. The cow’s location is then updated in real-time on the Traffic Gaaye app. After that, the app takes this location information, and by using AI, it calculates a route away from the cows to cut down on congestion and travel time.
This app allows users to save 15 minutes on average per trip and reduces emissions at peak hours. This shows how LI combined with AI can save time, money, and lives.
Case Study 2: Logistics and Transport
Have you ever wondered how Amazon can get you packages in only two days? Well, you might have guessed by now, since this is an article about LI and AI, LI and AI are probably involved. But, how do they use LI and AI?
Well, the problem that LI and AI solve in the first place is timing. For example, if your shipment from one vehicle to another is 20 minutes late, you are wasting 20 minutes of the time of the following vehicle because it’s just sitting there doing nothing. So this makes time the name of the game in logistics.
LI and AI are finding issues that slow down the supply chain. They do this by looking over a dataset, with many parameters, over a period of time. Then, the software finds that the bottleneck could be caused by, but not limited to:
The transfer of goods between different modes of transport (i.e., planes, ships, and trucks) 🛳️
Miscommuncations between various organizations (i.e., companies and governments)
Unnecessary large gaps in turnaround time ⏰
Lack of goods/raw materials arriving at a destination 🔩
The data analyst can then recommend solutions to these problems such as:
Change the mode of transportation ✈️
Better communication methods ☎️
Train an inexperienced workforce
Measure an orgnization’’s ability to provide these goods and diversify the source of goods.
(All the solutions are respective to the problems above.)
This software can help minimize the time supply chain managers spend on finding problems and reallocate this time into finding solutions for these problems.
“An AI-fueled approach to location intelligence can support those plans and foster growth in three ways: by automating processes, detecting patterns within large sets of data, and making predictions.”
Case Study 3: Store Placement
If you are a small franchise, the location of your next store matters. If you go into a place where there are no customers, you will get no money. If you place a Subway within five blocks of another Subway store in New York City, you will make no money. Location is crucial for a business, and finding the right place is vital for your business to survive.
Yet again, LI and AI can help with that. Esri, a GeoAI company, has developed a tool that takes in nearly 6,000 parameters about customers in a specific area and gives recommendations and predictions about the outcomes of store placement at a particular location. This can help small businesses grow quicker and more effectively.
Collecting & Analyzing Data
LI and AI are cool and all, but how does this work? Well, it’s pretty simple; first, you have to collect location data and other information, and then that data is processed using AI to give you actionable items to work on. But, the question now is how do you actually collect and process this data.
There is a tool developed by Esri, the leader in the space of AI and LI, called ArcGIS. This tool is what you use to collect and analyze the data. There already is existing spatial data for everyone to use, so you don’t need to collect everything from scratch. However, if you need to collect some data that isn’t already in the database, you can collect your own using the ArcGIS Collector. Which is a mobile app that can help you collect custom data points for your specific use case. Then to prepare this data for analysis, you can use ArcGIS pro, which will put all the information together.
For analyzing the data, you can still use the ArcGIS suite. You can import the data from ArcGIS Pro and insert it into ArcGIS online, which will compile all of the data and give you a visual representation for you to interpret the data and find the solution to your problem. If you want a more in-depth overview of the process, click here.
“The application of GIS is limited only by the imagination of those who use it”. ~ Jack Dangermond, Esri
Location Intelligence (LI) and Artificial Intelligence (AI) have massive potential in changing the way we do business and live
LI and AI have already been implemented in creative ways to solve problems as small as cow traffic to as large as logistics and transportation
Ersi, with their tool ArcGIS, is the basis of collecting and analyzing geospatial data