How can AIoT be applied in different industries?

1. What is AIoT ?

To put it simply, “internet” can connect different computers or mobile phones, while “internet of things”(IoT) is the connection of digital to physical objects such as cars, keys and lights. IoT systems are able to automatically collect various data such as image, temperature, pressure, global positioning system (GPS) location and barcode scanning through its IoT sensor, and automatically transfer this data through the Internet to a cloud server such as AWS, Microsoft Azure and Google Cloud. AIoT (artificial intelligence of things) is IoT with the association of AI - something that can help people make more insightful decisions through implementation of data analytics.

2. How does AIoT work?

An IoT device serves as an information collector, which has been advanced by significant developments in artificial intelligence, and machine learning that enable more granular insights and automated decision making from data provided by sensors, so AIoT is able to provide advanced analytics and insights for the organisation without human interference. The inclusion of AI algorithms and software-driven processes with IoT represents a very key opportunity to leverage the Artificial Intelligence of Things (AIoT) in many industries. By scanning IoT data, the AI system can identify patterns that a human being may not find.

>> See How Kodifly uses AIoT to analyze animal behavior. 

3. How can AIoT be applied in different industries?

3.1 In warehouse management

• Real-time inventory level tracking: AI-driven inventory tracking can minimize human intervention by scanning the data and automating the counting process. Distribution centers with IoT applications and artificial intelligence can count the real-time stock level accurately to track the product availability and unfulfillable orders, ultimately reducing inventory management errors.

• Minimize shortage/ surplus: With a machine learning model, businesses can learn from the recurring patterns. For example, AIoT-driven smart shelves can determine how long a specific group of products has been stored in the warehouse. The data collected by the IoT system can help to optimize the supply chain processes and prevent avoidable shortages or surpluses.

• Better utilization of warehouse spaces: Efficient use of warehouse spaces is important in the supply chain. By reviewing the usage patterns analyzed by AIoT, hot items can be allocated to the shelf that is closer to the access points to enhance storage efficiency.

3.2 In inventory management

• Food condition monitoring: To comply with the requirements of the Food Safety Modernization Act (FSMA), IoT solutions for temperature surveillance are necessary for transporting perishable goods as the IoT sensor can alert any conditions that don’t meet the specified parameters.

• Machine monitoring: Food production machines can be remotely monitored to schedule and plan for more efficient and cost-effective equipment maintenance and repair to  prevent unnecessary financial expenses.

3.3 In logistics & supply chains

Digital transformation in logistics to achieve smart supply chain management has emerged as the main answer to the complex challenges of warehouses nowadays.

With Artificial Intelligence of Things (AIoT), it can optimize and smarten the whole supply chain from manufacturing to transport and ultimately lower error rates in critical supply chain networks, bringing a huge breakthrough to supply chain management.

• Faster shipment: There are multiple shipment modes for product delivery. IoT system can provide real-time data analytics for logistics systems to update shipping routes for faster delivery.

• Process optimization: Intelligent transportation systems can analyze the real-time data from IoT devices for predictive analytics to identify the recurring problems during the process.

• Food condition monitoring during transportation: Real-time temperature monitoring in shipping ensures perishable items maintain up-to-standard temperatures and good condition from manufacturing to warehousing and distribution.

• Improve customer experience: Retailers can utilize data from connected vehicles to better plan for capacity and spare-parts inventory and increase customer loyalty by making the customer-service journey a bit smoother. According to research from Mckinsey & Company, IoT solutions in shipping after-sales service improvements could create $40 billion to $70 billion in economic value annually in 2030 in the broader transportation market.

3.4 In E-commerce

Online shopping is getting increasingly popular, and how IoT technology can help a business to grow both online & offline is noteworthy.  For example, some retailers have their business by region. After receiving the order from their e-commerce platform (e.g. Shopify, wooCommerce) some firms will leverage AIoT to scan the store with the product in stock in a specific region, and then the product will be delivered from the nearest store. It is expected that there will be a higher number of consumer goods using IoT technology to provide a higher quality of services for customers under the combination of online & offline strategies.

4. Case study

GreenPrice is a retail company specialized in retailing surplus and short-dated stock. With a huge quantity of orders and stocks, our AIoT-driven inventory management system optimizes restocking scheduling, estimates the time of inventory arrivals, and improves safety stock management. Tracking inventory using IoT systems helps GreenPrice determine the lead time needed to restock different types of products to avoid delays in delivery which will lead to a negative customer experience.

Retailers can use AIoT to understand conditions, locations and anomalies in a product’s journey. Having such data can help retailers identify issues such as conditions that might’ve damaged their merchandise.

>> See more client cases in smart inventory management