Importance of Quality Data Annotation in Logistics
Logistics is a very chaotic and time-intensive industry. Artificial intelligence (AI) plays a key role in this industry by assisting the smooth transportation of goods from one location to another. It assists in enhancing, refining, and analysing supply chain operations. Logistics can be seen at play right from the manufacturing floor to the front door. Logistics is also a field that has abundant data along with scope for gathering more data.
The creation of new AI solutions for supply chain disruptions involve consumption of a lot of resources. Since shipping and logistics need to be efficient, accurate, and capable of delivering best outcomes, right training data is required for producing the right outcome for your AI project. AI also assists retail merchants in obtaining a better knowledge of customer demographics and predicting how their customers will behave in the future.
Also, Internet of Things (IoT) devices are being used by shipping companies for collecting and analysing data regarding shipment of goods with the aim of:
- Tracking mechanical health
- Locating vehicles
- Transporting tools
Benefits of Artificial Intelligence in Supply Chain
AI offers certain benefits which are less visible than others. For instance, evaluating the effect of predictive analytics as per supply chain data might ultimately yield benefits. However, certain companies have indicated that there is a direct link between revenue shifts and the addition of AI within supply chains.
AI is no doubt a boon for mankind and has applications spanning across industries. It enables supply chain automation technologies (digital workers, warehouse robots, autonomous vehicles) to automatically execute mundane tasks in a risk-free fashion.
However, as per a survey by BCG, leaders in supply chain are yet to completely tap into the potential of AI. They discovered that the glitch was not with the technology, but its application i.e. where and how it was applied.
Six Ways AI can Revolutionize and Optimise Supply Chain
- Data Management: This involves training the AI systems for spotting inconsistencies, identifying patterns, and potential issues. The most difficult part of supply chain management is the overview and proper categorisation of data. Data management carefully observes trends or indications to identify issues with the aim of optimising supply chain.
- Efficiency: A word that can be used to adequately describe supply chain optimisation is ‘efficiency.’ Since supply chains are interlinked, a lag in one part of its network affects other parts as well. As AI lends an edge over humans and other computer based systems, issues can be handled promptly.
- Reconfiguration: Using AI, businesses can prevent possible threats since all businesses want to create supply chains to prevent possible inconsistencies or inefficiencies. Also, since this part of the company’s operations is often tedious, an AI system can obtain a broader view of the supply chain with the aim of optimising it by merging many suppliers of a product into one supplier or by identifying faster and cheaper methods of transporting materials between two networks.
- Capacity and Demand Forecasting: AI helps in overcoming various stresses relating to delays, backups, breakdowns due to unexpected demand and other issues. These programs are handy when it comes to delivering enhanced forecasting tools for fulfilling customer demand and capacity of a supply chain. It also enables businesses to pre-empt and add capacity at busy times for scaling down a supply chain at less busy times of the day with the aim of cutting down costs.
- Inventory Management: As per the company type, accurately managing inventory should be one of the most important aspects of maintaining a supply chain. This ensures that goods can move in and out of a company’s warehouse facility in a smooth fashion with protection from over or under stocking.
- Reducing Costs, Boosting Safety: AI assists in enhancing warehouse management by bringing down inefficiencies. There is increased safety with better management of warehouse. AI also automates some key aspects of work which are traditionally done by humans by removing them from the picture altogether.
Hence, logistics data annotation i.e. quality image and video annotation needs to be done at scale for precise, accurate, and efficient results. Any errors or delays can prove to be expensive. Since logistics is a field that’s gaining relevance, shipping and trade can result in making or breaking the global economy. Apart from free trade and enterprises, governments and militaries also rely on logistics and supply lines. Selecting the correct video annotation services for computer vision is critical to an AI project. Hence, it’s wise to outsource your data annotation services to prevent issues and supply chain disruptions in your dataset.
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