GIS-BASED AI AND LOCATION INTELLIGENCE FOR BUSINESS AUTOMATION

Introduction

Artificial Intelligence took a significant step that was emerging independently in GIS. GIS and AI have converged substantially over the last decade. GIS is a renowned technology that provides large data sets and a diverse range of AI applications. Companies are better prepared to achieve growth strategies, strong customer interactions, effective asset management, and much more reliable vulnerability assessments with smart maps that add some context to Intelligence insight.

AI-powered systems can process this vast amount of data and forecast weather consequences soon. Smart maps based on GIS encapsulate those forecasts, allowing corporate executives to see how climate change is affecting specific industry locations, such as office spaces, stores, distribution facilities, and transportation systems, in the coming years.

Internal Services: AI is enhancing operational processes in a multitude of ways. AI-based facial recognition systems enforce employee access to secure areas in some workplaces. AI-powered predictive maintenance systems assist in determining the best service schedule for delivery truck fleets. But rather AI-infused bots are now functioning HR tasks used to mandate human involvement, such as educating staff.  

Interactions with Customers: AI is bringing intelligence to certain customer-facing tasks. Several more recommendation systems, for example, use AI to recommend appropriate products or respond to a specific user who resides in a particular location. It serves as the foundation for security systems that detect a fraudster's voice sign or potentially malicious online activity in live time and deny the individual access to an online account. It also facilitates chatbots, which connect with consumers worldwide online daily.

Business Marketing: AI can predict movements in supply and demand and how businesses might adapt, which is useful for top management and judgment looking for expert advice. To forecast sales, marketing mix, and staff numbers for the near future, the technology can easily filter through customer purchasing behaviors and attributes such as planned competitor stores.

Location Intelligence

Location intelligence, acquired by the use of a geographic information system (GIS), provides companies with the opportunity to map, analyze, and share data in the context of a specific location. The conceptual model and analysis of geospatial data are used to achieve location intelligence (LI).  Analysis of geospatial data improves comprehension, insight, decision-making, and forecasting.

Enterprises can use intelligence tools to determine where an event occurred, explain why it occurred, and obtain insights into what influenced it by adding layers of geospatial data to a smart map or navigation system, such as demographics, traffic, and weather. Several companies depend on geographic information system (GIS) technology to generate location intelligence as a component of a digital transformation.

The primary objectives of AI techniques in GIS applications are as shown in:

• Enhance specific methods in spatial relationships.
• Gain access to the forecast validity and suitability of spatial modeling techniques both individually and as an integrated approach for various datasets.
• Using rule filtration and factor sensitivity trials, AI techniques can gather information into critical spatial operations and processes.

AI applications in GIS

• Optical character recognition (OCR)
• Recognition of faces.
• Man-made creativity.
• Robotic vision.
• The use of virtual reality.
• Image processing
• Voice recognition
• Handwriting recognition