What could be better than to unwind with your favorite music playlist? Some may have a different approach to relaxation, but most of us including myself turn towards music. One voice command and the voice assistants like Alexa, and Siri play the song and perform many such other tasks. Today, just like any other day, while I was sipping on my cup of coffee with music that created a perfect ambiance like that of a cafe, I wondered what else could these voice assistants do besides sending text messages, making schedules, making calls, and playing music, and videos, etc. With this thought in mind, I started my day!

On my way to work, there is this pharmacy, which is never idle. Constant visitors waiting for their turn to buy prescriptions and other necessities. Today when I passed by, it struck me that this answers my query that had been left unanswered earlier in the morning.

A voice assistant that can make shopping more convenient for customers.

We can develop our voice assistant with enhancements over the existing ones. Besides performing the previously mentioned tasks, this assistant can find its application for greater purposes. Before we get into what I had to say about upscaling the assistants. Let us begin by understanding them.

The rate at which this industry has advanced is astounding, and the future is for us to witness. Voice assistants are a part of our everyday lives, learning from the subtleties of voice.

Recently available technologically advanced Bluetooth AirPods and headphones provide better sound quality and in-built noise cancellation, this enables the users to have a better interaction with the assistants even while they have some other task at hand. Natural Language Processing, also known as NLP, is used by these digital assistants. NLP is concerned with human-machine interactions, or, to put it another way, teaching machines to comprehend and analyze human language to execute essential tasks.

NLP enables machines to interact with one another in a variety of ways, including but not limited to speech and text, utilizing natural human language.

After clearing any noise disturbances, the voice assistants capture the voice, and once a wake word, such as “ALEXA,” is discovered, the process is initiated, and a signal is delivered to cloud services, where the audio is translated to text. Following that, a certain skill is triggered after recognizing an invocation name, which might be a query, action, or order. Finally, the assistants deduce the purpose based on the utterance, which are the sentences used by a user to express the instruction. If necessary, the Alexa voice service sends a request to a third-party server.

Let’s get started with upscaling these voice assistants now that we’ve covered the basics. So, with the initial goal of making the process easier for consumers, a voice assistant coupled with the shop’s inventory database and the user’s app might address concerns such as excessive waiting time and others. The core thought process is that if customers want a product, they should first choose the appropriate store and then ask the voice assistant for product details. The voice assistant can then respond with the available quantity and other details. If the product is available, the user may purchase it right away, and if it isn’t, the user can request it from one of the available suppliers. This not only saves time but also alleviates the irritation that comes with poor management.

A peek into real-life
Let’s deep dive into the real-life implementation of the above-discussed voice assistant for a better understanding of how it works. For this let us consider the example of pharmacy which I mentioned earlier. For sake of simplicity let us consider one of the many available products, medicine.

If you take a closer look at the packaging of any medicine, you can easily find the product code usually in the form of a barcode, its title, the manufacturing, and expiry date, the number of tablets per strip, price, and much more. Another important information for the store owners is the available quantity of sellable medicines, that is the one which has not exceeded the expiry date. Taking this discussion further let us consider a few use cases.

Instant updates on requested details
Due to the sheer difficulty around the pronunciation of complicated medications, users are recommended to request information using the product code; nevertheless, supplying proper pharmaceutical names will also yield the necessary results.

The voice assistant initially conducts a query to verify the available amount and expiration date after receiving a request for information about a specific medicine from the user. If the amount is less than zero, the result is an out-of-stock message. If the quantity of medicine is more than 0 yet the expiration date has exceeded, an alert is sent to the medical representative. Finally, if the medicine is in stock and sellable, the output sent in the form of a response to the users includes the title and available quantity.

B2B made easy

Let us analyze the case of B2B, or business to business information exchange, now that we have a better understanding of how fundamental queries work. Local pharmacists can simply pre-order medicines in bulk quantities using the procedure outlined above. The only difference is that there will be an additional input field of the required quantity. After confirming the first two conditions, the voice assistant will check to see if the primary suppliers have enough stock to meet the demands. If satisfied, users will receive an affirmative reply.

Get notified about inadequate stock with alerts
A use case common to the earlier two discussed use cases. If the individual consumer or local pharmacists receive an output response indicating a lack of available medicine or insufficient quantity, they should contact the supplier. They may use voice assistants to instantly make a request, which will generate a demand message to all of the key suppliers, requesting greater supply. Depending on the inventory status of these primary suppliers they can revert.

The demand and supply chains can run smoothly with the use of a single application.

Track your inventory hassle-free
As mentioned earlier, a medicine that has exceeded its expiry is found, and an alert is sent to the medical representative. With these constant updates, it is easy to track the medicines that have exceeded the expiry date along with their quantity. This makes it simpler for the pharmacist to request stock as and when required.

Now, to respond to your query, how do you link voice assistants to the medical shop database? The solution is to use an API. The proper output will be delivered once the essential inputs have been obtained. Voice assistants then translate these text outputs into audio communications.

In these discussions we have considered four major use cases, there is much more worth your attention. These voice assistants are more useful to shops with constant customer engagement as compared to ones with occasional visitors. With this, the tedious tasks are automated, saving time and ensuring good customer service. A further extension could be that the shop employees use these voice assistants to locate a particular medicine, which can increase working efficiency. In the future orders can be placed using these voice assistants. The above discussed upgraded voice assistants are cost-effective.

Conclusion
You must have realized by now the magnitude to which these voice assistants may change our lives, and it is clear that in the not-too-distant future, their involvement with our lives will be far greater than it is now. We addressed the use in pharmacy in this article, but it might be applied to other sectors as well. Currently, voice assistants cannot provide a user experience that is comparable to having a real, meaningful conversation with a human.

However, I am confident that with enough time, even this can be accomplished. It’s vital to remember that there’s always room for growth, and even if these assistants are trained to work in a variety of languages, they won’t be able to comprehend the task effectively if they’re bombarded with a variety of languages. The end output may be gibberish and unappealing to the user. To address this, more work is essential. In the next article, we will discuss in detail the technical implementation till then Happy Reading!