Intelligent vending machine serves fast growing market
- Autore:Ella Cai
- Rilasciare il:2017-06-29
Developments in control electronics will help ATM sensors to recognise you and the vending machine to serve you better, writes Fabrizio Petris of Omron Electronic Components Europe.
That growth is being driven by a new class of unit: the intelligent vending machine, which marries the convenience and accessibility of instant, on-the-spot transactions with the tailored, entertaining and connected retail experience that customers now expect.
According to a March 2017 report from US-based Grand View Research, this market is expected to reach $11.84bn by 2025.
Every vending machine will encompass electronic systems to facilitate the interaction with the user, to control product and cash dispensing and to manage energy use.
The technology to create this new breed of intelligent vending machines includes sensors to identify the customer, presence detection and reliable cash counting mechanisms, as well as remote reset switches.
What is an intelligent vending machine?
Essentially the intelligent vending machine delivers a purchasing experience that is personal and individual for each user.
The machines can be tailored to the application, in terms of colour, size, space and dispensing rate, which is essential as roll-outs can be quite small. They are internet of things‑compatible and are fully connected, with cloud‑based server support, scanning tools and value-added services.
Vendors can use the internet to update content for their interactive platforms and to present custom advertising.
While the range of goods on offer is huge, food and beverage is one of the largest markets: especially hot drinks.
Dublin-based Research and Markets found that the hot drinks segment dominates the industry, accounting for more than 62% of the overall volume. Many drinks and food machines are located in offices, as they make it easy for employees to grab a quick snack or drink.
Identifying the customer
Vending machine manufacturers recognise that this interaction is an essential part of the experience, and can be monetised. For example, their market research may show that a specific snack appeals strongly to customers aged 20-25 – so a tailored offer to these customers might have an impact. A quite different offer might appeal to the 60-plus age group, so a vending machine needs to emulate something that a human does quite easily and naturally – it must be able to identify the customer.
Fitting vending machines with a camera is straightforward and inexpensive, but the challenge is enabling it to then interpret what the camera sees.
Fortunately, consumer electronics is already providing a solution. Phones can recognise their owner’s faces, and vending machines can make use of the same algorithms and technology.
Omron Figure 1 - HVC-P2 B5T face recognition moduleImplementing them is a challenge though – vending machines are produced in tiny volumes compared to phones, and have a significantly different architecture. The success of the design depends critically on the use of good algorithms that deliver a reliable result without using excessive system resources. Even well-designed algorithms will be processor- and memory-intensive – and adding vision will demand additional system resource.
The Omron HVC face recognition module (pictured right) is aimed at such applications, available in low volumes and can integrated by designers who will not need to understand the complex algorithms used to analyse the image, or the optical design. HVC builds on the Omron Okao Vision software, a proven set of image recognition algorithms used in over 500 million digital cameras, mobile phones and surveillance robots around the world. Key features of the module include speed and consistency of response, and the distance over which it can take readings.
For example, HVC can capture an image of, detect and recognise a face and provide information like age, gender and mood over a distance of 1.3m in 1.1s. It will also indicate a confidence level with its reading.
The module is a fully integrated, plug-in solution. The developer need only look at the outputs and configure the system to make appropriate decisions depending on their status.
Detection mechanisms
Intelligent vending machines offer a widening range of goods and need to adapt quickly to changing retail needs.
Drinks vending machines offer a particular challenge, as they need to detect the presence and level of different liquids, some of which may be clear, and the presence or absence of cups, which again could be made from clear plastic. The fact that these liquids may be hot and pose a safety hazard increases the importance of accurate and reliable detection.
Although conventional photo micro sensors (PMSs) are often suitable, they are known to struggle with many types of surface. Transparent objects and liquids have always been hard to detect, as have mirrored, diffuse and deep black surfaces.
Omron Figure 2 - B5W light convergent sensorOmron’s B5W light convergent reflective sensor (pictured right) detects target objects much more reliably than general reflection photo sensors, even those that are often a challenge, such as reflective, transparent, diffuse or black surfaces.
The sensor’s convergent light beam can be accurately set to trigger at the presence of an object within a tightly specified target area, and ignore any objects in the background or foreground.
These sensors are equally suitable for contactless detection of clear or coloured liquids in transparent tanks and feature a combination of a cylindrical and a non-spherical lens.
Cash counting
The latest high-resolution micro displacement sensors can greatly increase the reliability of these mechanisms, offering contactless measurement of the thickness of paper and multi-feed detection through minute changes in the location of light reflected from the object.
For example Omron’s Z4D micro‑displacement sensor (pictured below) can resolve 10μm – one tenth the diameter of a human hair.
The exceptional resolution is based on a proprietary optical design using the triangulation.
Omron Figure 3 - Z4D micro displacement sensorThis structure achieves good and stable linearity between the output voltage and distance, simplifying the design of the host circuit.
Standby power design
Intelligent vending machines are subject to power control directives like the EU ErP Ecodesign Directive, which specifies that the power consumption of equipment in standby mode should not exceed 0.50W, unless the equipment has a status display, in which case 1W is permissible.
This applies particularly to table‑top machines such as office coffee machines which are used less intensively and can be left to switch off when not in use – over night, for example. To support this requirement, Omron has introduced the industry’s smallest remote-reset rocker switch supporting zero-standby power design (pictured below).
Figure 4 - A8GS smallest remote-reset rocker switchIt can be controlled remotely and is offered in a version with a delayed-off feature to support safe system shut-down. With this switch, the power to the system is maintained when the switch is returned to the off position.
The system is then powered down by an external signal after an interval determined by the designer. This prevents issues with data loss or circuit damage through forced power off by the user, and can help safer application design.
Vending machines have been popular and convenient for many years, allowing the impulse-purchase of goods instantly at any time. In an increasingly 24/7 world, with staff costs increasing, they are likely to become more popular as time goes on.
New electronic technologies are enabling the intelligent vending machine, a development that will enable this well-established concept to remain relevant in the age of internet of things and the cloud.
The vending machine is a relatively unrecognised, but fast growing market opportunity for the electronics industry.
That growth is being driven by a new class of unit: the intelligent vending machine, which marries the convenience and accessibility of instant, on-the-spot transactions with the tailored, entertaining and connected retail experience that customers now expect.
According to a March 2017 report from US-based Grand View Research, this market is expected to reach $11.84bn by 2025.
Every vending machine will encompass electronic systems to facilitate the interaction with the user, to control product and cash dispensing and to manage energy use.
The technology to create this new breed of intelligent vending machines includes sensors to identify the customer, presence detection and reliable cash counting mechanisms, as well as remote reset switches.
What is an intelligent vending machine?
Essentially the intelligent vending machine delivers a purchasing experience that is personal and individual for each user.
The machines can be tailored to the application, in terms of colour, size, space and dispensing rate, which is essential as roll-outs can be quite small. They are internet of things‑compatible and are fully connected, with cloud‑based server support, scanning tools and value-added services.
Vendors can use the internet to update content for their interactive platforms and to present custom advertising.
While the range of goods on offer is huge, food and beverage is one of the largest markets: especially hot drinks.
Dublin-based Research and Markets found that the hot drinks segment dominates the industry, accounting for more than 62% of the overall volume. Many drinks and food machines are located in offices, as they make it easy for employees to grab a quick snack or drink.
Identifying the customer
The barista in the coffee shop will naturally aim to greet a business executive, an elderly lady and a teenager differently. More engaged staff may try to tempt them with a croissant, a cake or a healthy snack, depending on their knowledge of what this kind of customer or this individual customer will normally buy.
Vending machine manufacturers recognise that this interaction is an essential part of the experience, and can be monetised. For example, their market research may show that a specific snack appeals strongly to customers aged 20-25 – so a tailored offer to these customers might have an impact. A quite different offer might appeal to the 60-plus age group, so a vending machine needs to emulate something that a human does quite easily and naturally – it must be able to identify the customer.
Fitting vending machines with a camera is straightforward and inexpensive, but the challenge is enabling it to then interpret what the camera sees.
Fortunately, consumer electronics is already providing a solution. Phones can recognise their owner’s faces, and vending machines can make use of the same algorithms and technology.
Omron Figure 1 - HVC-P2 B5T face recognition moduleImplementing them is a challenge though – vending machines are produced in tiny volumes compared to phones, and have a significantly different architecture. The success of the design depends critically on the use of good algorithms that deliver a reliable result without using excessive system resources. Even well-designed algorithms will be processor- and memory-intensive – and adding vision will demand additional system resource.
The Omron HVC face recognition module (pictured right) is aimed at such applications, available in low volumes and can integrated by designers who will not need to understand the complex algorithms used to analyse the image, or the optical design. HVC builds on the Omron Okao Vision software, a proven set of image recognition algorithms used in over 500 million digital cameras, mobile phones and surveillance robots around the world. Key features of the module include speed and consistency of response, and the distance over which it can take readings.
For example, HVC can capture an image of, detect and recognise a face and provide information like age, gender and mood over a distance of 1.3m in 1.1s. It will also indicate a confidence level with its reading.
The device implements the Okao software on a hardware platform that has a camera, processor and data interface optimised in terms of its digital and optical design for this application.
The module is a fully integrated, plug-in solution. The developer need only look at the outputs and configure the system to make appropriate decisions depending on their status.
Detection mechanisms
Intelligent vending machines offer a widening range of goods and need to adapt quickly to changing retail needs.
Drinks vending machines offer a particular challenge, as they need to detect the presence and level of different liquids, some of which may be clear, and the presence or absence of cups, which again could be made from clear plastic. The fact that these liquids may be hot and pose a safety hazard increases the importance of accurate and reliable detection.
Although conventional photo micro sensors (PMSs) are often suitable, they are known to struggle with many types of surface. Transparent objects and liquids have always been hard to detect, as have mirrored, diffuse and deep black surfaces.
Omron Figure 2 - B5W light convergent sensorOmron’s B5W light convergent reflective sensor (pictured right) detects target objects much more reliably than general reflection photo sensors, even those that are often a challenge, such as reflective, transparent, diffuse or black surfaces.
The sensor’s convergent light beam can be accurately set to trigger at the presence of an object within a tightly specified target area, and ignore any objects in the background or foreground.
These sensors are equally suitable for contactless detection of clear or coloured liquids in transparent tanks and feature a combination of a cylindrical and a non-spherical lens.
Cash counting
Despite the increasing popularity of contactless payment, many customers still like to present cash. Increasingly, machines need to accept notes and to return them in change.
The latest high-resolution micro displacement sensors can greatly increase the reliability of these mechanisms, offering contactless measurement of the thickness of paper and multi-feed detection through minute changes in the location of light reflected from the object.
For example Omron’s Z4D micro‑displacement sensor (pictured below) can resolve 10μm – one tenth the diameter of a human hair.
The exceptional resolution is based on a proprietary optical design using the triangulation.
Omron Figure 3 - Z4D micro displacement sensorThis structure achieves good and stable linearity between the output voltage and distance, simplifying the design of the host circuit.
Standby power design
Intelligent vending machines are subject to power control directives like the EU ErP Ecodesign Directive, which specifies that the power consumption of equipment in standby mode should not exceed 0.50W, unless the equipment has a status display, in which case 1W is permissible.
This applies particularly to table‑top machines such as office coffee machines which are used less intensively and can be left to switch off when not in use – over night, for example. To support this requirement, Omron has introduced the industry’s smallest remote-reset rocker switch supporting zero-standby power design (pictured below).
Figure 4 - A8GS smallest remote-reset rocker switchIt can be controlled remotely and is offered in a version with a delayed-off feature to support safe system shut-down. With this switch, the power to the system is maintained when the switch is returned to the off position.
The system is then powered down by an external signal after an interval determined by the designer. This prevents issues with data loss or circuit damage through forced power off by the user, and can help safer application design.
Vending machines have been popular and convenient for many years, allowing the impulse-purchase of goods instantly at any time. In an increasingly 24/7 world, with staff costs increasing, they are likely to become more popular as time goes on.
New electronic technologies are enabling the intelligent vending machine, a development that will enable this well-established concept to remain relevant in the age of internet of things and the cloud.
