Machine vision with low-cost Camera Modules

Capture the flag with a GPS, RFID and LoRa twist

A tabletop bowling game with automated scoring

BLOG HOME

Machine vision with low-cost camera modules

ARDUINO TEAM — June 24th, 2020

If you’re interested in embedded machine learning (TinyML) on the Arduino Nano 33 BLE Sense, you’ll have found a ton of on-board sensors — digital microphone, accelerometer, gyro, magnetometer, light, proximity, temperature, humidity and color — but realized that for vision you need to attach an external camera.

In this article, we will show you how to get image data from a low-cost VGA camera module. We’ll be using the Arduino_OVD767x library to make the software side of things simpler.

Hardware setup

To get started, you will need:

• Arduino Nano 33 BLE Sense with headers
• OV7670 CMOS VGA Camera Module
• 16x female to female jumper wires
• A microUSB cable to connect to your Arduino

You can of course get a board without headers and solder instead, if that’s your preference.

The one downside to this setup is that (in module form) there are a lot of jumpers to connect. It’s not hard but you need to take care to connect the right cables at either end. You can use tape to secure the wires once things are done, lest one comes loose.

#machine learning #camera

What is GEEK

Buddha Community

Optimizing A Low-cost Camera for Machine Vision

Arduino recently announced an update to the Arduino_OV767x camera library that makes it possible to run machine vision using TensorFlow Lite Micro on your Arduino Nano 33 BLE board.

If you just want to try this and run machine learning on Arduino, you can skip to the project tutorial.

The rest of this article is going to look at some of the lower level optimization work that made this all possible. There are higher performance industrial-targeted options like the Arduino Portenta available for machine vision, but the Arduino Nano 33 BLE has sufficient performance with TensorFlow Lite Micro support ready in the Arduino IDE. Combined with an OV767x module makes a low-cost machine vision solution for lower frame-rate applications like the person detection example in TensorFlow Lite Micro.

#arduino #machine learning #camera library #machine learning #machine vision #tensorflow lite for microcontrollers #tiny machine learning

Improve Your Cost Management with AWS Saving Plans

The adaptability and flexibility of today’s cloud services present a lot of opportunities to cut infrastructure costs. Amazon Web Services and its plethora of services let you set up any kind of cloud environment for any type of application, without forcing you to make long-term commitments. At the very least, you don’t have to make a big initial investment to set up your cloud environments.

AWS resources are designed to make deploying cloud-native applications easy and affordable. Affordability is always important for businesses because cost-efficient applications guarantee higher returns on cloud investment. The way AWS services are set up allows for easy scaling of apps and cloud resource usage, but keeping your cloud environment efficient is not without its challenges.

#aws #amazon web services #cost #cost optimization #cost analysis #cost management #cost analytics #aws costs

Machine vision with low-cost Camera Modules

Capture the flag with a GPS, RFID and LoRa twist

A tabletop bowling game with automated scoring

BLOG HOME

Machine vision with low-cost camera modules

ARDUINO TEAM — June 24th, 2020

If you’re interested in embedded machine learning (TinyML) on the Arduino Nano 33 BLE Sense, you’ll have found a ton of on-board sensors — digital microphone, accelerometer, gyro, magnetometer, light, proximity, temperature, humidity and color — but realized that for vision you need to attach an external camera.

In this article, we will show you how to get image data from a low-cost VGA camera module. We’ll be using the Arduino_OVD767x library to make the software side of things simpler.

Hardware setup

To get started, you will need:

• Arduino Nano 33 BLE Sense with headers
• OV7670 CMOS VGA Camera Module
• 16x female to female jumper wires
• A microUSB cable to connect to your Arduino

You can of course get a board without headers and solder instead, if that’s your preference.

The one downside to this setup is that (in module form) there are a lot of jumpers to connect. It’s not hard but you need to take care to connect the right cables at either end. You can use tape to secure the wires once things are done, lest one comes loose.

#machine learning #camera

5 Latest Technology Trends of Machine Learning for 2021

Check out the 5 latest technologies of machine learning trends to boost business growth in 2021 by considering the best version of digital development tools. It is the right time to accelerate user experience by bringing advancement in their lifestyle.

#machinelearningapps #machinelearningdevelopers #machinelearningexpert #machinelearningexperts #expertmachinelearningservices #topmachinelearningcompanies #machinelearningdevelopmentcompany

Visit Blog- https://www.xplace.com/article/8743

#machine learning companies #top machine learning companies #machine learning development company #expert machine learning services #machine learning experts #machine learning expert

Banking App Development Cost - 8 Hidden Factors

Since 1994, Digital banking has been here. It is a very long time, but digital banking through mobile devices is entirely new to the banking industry. It all started when Atom became the first digital-only bank in the UK.

Nowadays, Tech-savvy customers expect corporations to support their digital movement, and because of this, almost every industry has adopted technologies to stay relevant with these modern customers. Most of the newbies who plan to develop a banking app have two questions in mind: “What is the cost of developing a banking application” and “Which hidden factors affect the cost of developing a banking app?”

You can get all the answers to these questions here, because this article will take you through the cost of developing a banking app, the features of banking apps, and much other pertinent information. After reading this, you will be able to plan better for your mobile banking app development. But before directly jumping into the cost of mobile banking app development, let’s take a look at the global digital payment market size of mobile banking.

Global Digital Payment Market Size

According to GlobalNewsWire, by 2026, the Global Digital Payment Market size is estimated to reach $175.8 billion, rising at a market growth of 20% CAGR during the forecast period.

Around 23% of millennials use mobile banking apps daily.
Around 49.2% of total smartphone users use mobile banking apps.
41% of Americans said that mobile banking apps had minimized their concerns about managing finances.

Data Source: Statista

As you can see, the data clearly indicates that the percentage of smartphone users are increasing day-by-day. Therefore, by engaging in your own mobile banking app development currently, you will be able to take advantage of the growth in mobile users. But, the cost of developing a banking application depends on so many factors like the platform, features, technologies, and so on.

Mobile banking app development cost

Cost of developing a banking app depends on various factors. To give you a rough idea of the mobile banking application development cost, the total development time for a fully-featured app sums to 3760 hours. Considering hourly rate for fintech projects of $25, the cost of developing a feature-loaded banking app stands around $94k.

Banking Application Development Cost depends on different phases such as:

• Research and Planning
• UI/UX Design
• Development
• Testing
• Maintenance and Support

8 Hidden Factors of Costs of Mobile Banking App Development

1. Push Notifications

It’s not easy to imagine an app that does not utilize this necessary mobile capability. Push notifications always increase your users’ engagement with your mobile banking app and encourage the desired action. Push notifications are of three types:

1. Transactional notifications notify users about their account updates.

2. The Application-based notifications indicate when the mobile banking app requires the user’s attention, whether related to the password change requests or document submissions.

3. Promotional notifications are to grab the attention of customers to offer discounts and attractive deals.

2. Chatbot Integration

For most users, mobile banking has a steep learning curve, and due to that, the customer will require immediate assistance on various occasions. Hence, creating a chatbot for customer service is the best way for many institutions to improve their customer service availability. The chatbots will save you a lot of time and money, whilst providing customer support 24/7. But this feature has a separate development process, and therefore you have to pay separately for this.

3. Servers

Servers are where your mobile banking app will be hosted. If you are not with the largest enterprises, you will want to outsource hosting from Amazon, Azure, or Google, which will result in more costs.

4. Content Delivery Network

A CDN is a system that is used to deliver content to the app based on the origin of the content, the content delivery server, and the geographic location of the particular user. In simple words, if you have users across the globe, and they have to keep coming back to one far off location to access the content, then the app will not perform in a good way. So, if you want your mobile banking app to perform effectively, you should use a content delivery network, because it reduces the app loading time and also increases the responsiveness of the app.

5. Development Tools

If you want to use paid deployment tools like iBuildApp, Appy Pie, and IBM MobileFirst, to develop your mobile banking apps, you will need to subscribe to them over the lifespan of your app. This will also affect your banking app development cost.

6. Android and iOS Updates

As we all know, both platforms constantly release updates, and those updates require maintenance. Depending on the extent of maintenance required, the cost in the long-term can sometimes be significant.

7. APIs

Every mobile app usually has multiple third-party APIs that they interact with, especially at the enterprise level. If you make changes to any of these applications, they will require periodic maintenance of your APIs. For instance, Facebook updated their API version four times in 2016; now, what if you want to integrate with Facebook? You will need to update your app to accommodate those changes.

8. Bugs

As you know, every app has bugs, and not even a single developer can assure you that there will be no bugs in the future in your app. It’s just that sometimes they go undiscovered for months or even years. User communities are not kind to apps that are slow to address the issues that they have reported.

Conclusion

The cost of banking application development not only depend on the features of the banking application, but they are also heavily affected by the hidden factors I have mentioned. The primary issue with mobile banking app development cost is the amount of individual components that you need to gather. Each of them can cost thousands of dollars, and these costs will continue throughout the lifespan of your app. However, the rewards that come from a successful mobile banking app development project are huge.

Pro Tip: The cost of developing a banking application greatly depends on the hourly rates of programmers and the expertise of the team. FinTech experts are able to complete these projects much more efficiently.

#banking app development cost #banking application development cost #cost of developing a banking app #cost of developing a banking application #mobile banking app development cost #mobile banking application development cost