Livestock has the longest history of traditional industry.

The technological development of Industry 4.0, to a certain extent, has also promoted the industrial transformation of the animal husbandry industry.

How to make livestock management more "intelligent" "cutting-edge livestock" "smart farm". This kind of vocabulary appeared in the eyes of people.

In order to improve the efficiency of work, many farmers have also begun to develop IoT solutions that can be applied to their own animal husbandry operation system.

Combining the current technology to optimize the traditional breeding scheme, it has a considerable promotion effect on the management of the livestock life cycle and sales.

Our project manager learned from a pig breeding base in Japan that the basic pig breeding requires a macroscopic process of raising, achieving weight detection, screening, and selling.

In view of the optimization of the efficiency of animal husbandry nuclear operations, combined with actual operation scenarios.

Pigs are sorted according to their status

Rough judgment is easy to make mistakes and missed checks.

Pig weight decetion

Pig weighing scales are relatively difficult to use and ineffective.

Human monitoring of feeding status

Manual inspection is a big problem for large farms.

Livestock statistics

Livestock quantity statistics is a very important thing, but it is cumbersome and labor-intensive at high frequencies.

Through the analysis of user pain points, M5 puts forward some suitable solutions for some problems currently encountered in the livestock industry.

For the preliminary sorting of the pigs that meet the standards, we used the ESP32-CAM wireless WIFI camera program to take pictures of the livestock in the breeding pen at regular intervals and upload them to the cloud to perform AI analysis on the individuals who meet the standards. Tracking marks, the automatic output of corresponding list sets, prompting the breeder to weigh the individuals in the set for the next step of testing. /p>

An embedded "weighing area"(embedded weighing sensor and high-precision ADC conversion core, combined with the IoT main control CORE to realize wireless data upload) is deployed at a fixed point in the pigsty. The weight information can be automatically recorded by pulling the livestock to the specified area, forming a streamlined operation and accelerating work efficiency. /p>

AI sorting to be tested

Wireless WIFI camera + cloud AI analysis plan, a form, feedback all results.

Deploy a dedicated area for weighing

Drive livestock into the dedicated weighing area detection area, form a weighing queue, and weigh efficiently.

Real-time monitoring of feeding status

Through the camera image, the status of the pigsty is detected in the background, and the number of inspection personnel is reduced.

Intelligently count the number of livestoks

Automatically figure out number by detection algorithms based on camera images.

Out-of-stock (OOS), also known as Stockouts, are among the most frustrating experiences for online and in-store shoppers.

Retailers are missing out on nearly $1 trillion in sales because they don't have on hand what customers want to buy in their stores, according to a study conducted by IHL Group.Shoppers encounter out-of-stocks as often as one in three shopping trips, according to the report.(source)

And almost a third of shoppers ended up turning to Amazon when the product they wanted wasn't in stock at their local store.

Loss of retail orders during an OOS period

During the OOS period, it is easy to lose potential retail orders.

Lack of data analysis source

Record and analyze the impact of shelf area on merchandise sales.

Labor resources consuming

A large number of shelf management staff need to repeat inspections and replenishment of OOS products.

Lack of efficient shelf stock replenishment tips

Originally manual inspection, temporary warehouse replenishment.

Applying with Low-power consumption Timer Camera launched by M5Stack, it can effectively take pictures of shelves at regular intervals, connect to the WIFI network, upload to cloud server, and analyze the inventory of shelves with deep learning algorithm. Instantly analyze and alert the staff with the OOS products and locations.

Compared to the traditional operation procedure, Volt hardware solution simplifies the inspection process for store managers, and avoids the potential loss of orders caused by products shortage, from store to store. That is also a big help in freeing up labor resources.

Simple, reliable, and highly integrated TimerCAM can instantly and efficiently deploy on-site to monitor on-shelf data.

Smart on-shelf inventory replenishment alert

The system is applied for timing identification, alerting the staff for OOS products and shelf locations, to replenish products in time.

Data Statistics/Graph Analytics

Record and analyze the impact of shelf location to product sales.

Labor resources are allocated reasonably

Free up more working hours for labor resource.

Low-power consumption Wifi camera on-shelf monitoring

The ultra-low power consumption camera is programmed to wake up regularly, and the system can work continuously for more than a year without replacing battery.

Weather forecast models are often used to simulate the weather and predict future weather conditions. However, weather forecasting models do not give completely accurate weather forecasts. This is why weather forecasting software usually presents the probability of precipitation (rain/snow) as a percentage.

In recent 20 years, extreme weather events such as droughts and floods occur more frequently and with greater severity as forecast models fail.

Increasingly erratic weather patterns are already having a significant impact on the lives of humanbeings and food security around the world. Accurate climate and weather information helps people to be able to plan ahead and adapt to climate change. However, to improve weather forecasting, it is first necessary to be able to monitor the weather.

Climate disaster causes huge losses

Weather conditions are a very important part of people's lives, from clothing for going out to life safety. It can be extremely dangerous in the event of severe weather. In a new report released by the United Nations, the number of global climate disasters has risen sharply from 2000 to 2020, with extreme weather becoming the most significant source of disasters in the 21st century.

Difficult to obtain accurate weather data

The world is undergoing a digital transformation. Data is playing an increasingly important role in improving people's lives. Weather data is vital to livelihoods, agriculture, navigation, transportation, traffic, energy and other industries. There are many limits to building a traditional weather station, such as the high cost and the complexities of deployment techniques. It is difficult for people to obtain accurate local weather information for planning and preparation by setting up a traditional weather station.

Weather data of remote areas is also important

Remote and sparsely populated areas are often under-deployed. Yet these places’ weather data is more valuable than we think, for example, Tibetan Plateau’s data is valuable for studying global climate change.

Technology can help improve weather forecasts in a variety of ways. One of them is via the weather network– WeatherXM. WeatherXM is a weather networking community leveraging Web3, IoT, and machine learning technologies to bring about a paradigm shift in weather data collection and positively impact the planet and the lives of millions of people on it. As a partner of M5Stack, WeatherXM is using Volt hardware to collect high-quality, hyperlocal weather data and make it generally available, to create impactful change for industries that rely heavily on accurate weather readings.

WeatherXM, based in Greece, is a company to make a global weather network for people to get hyper-local accurate forecasts, suitable for agriculture, energy, outdoor sports, maritime, or any other use case. It can build small weather stations that can be deployed in previously inaccessible areas and collect valuable information. And WeatherXM has developed a number of advanced weather and environmental solutions and delivered thousands of smart weather stations to customers around the world. And now it’s currently producing more to meet customers’ demand and expand its range with a new version that connects more easily with M5Core2, which is much easier for users to deploy.

The most important part of this Web3-compatible, integrated solution is M5Core2. M5Core2 has a 2.0" integrated capacitive touch screen to provide a smoother human-computer interaction experience. With the function of GPS + LoRA + WiFi communication, it features low-power consumption, easy deployment, remote transmission, real-time data transmission and OTA functions. Moreover, the device is equipped with a built-in ATECC608 hardware encryption chip, which can enhance the security of the device's IoT communication process by means of hardware-level keys. Users can view the data at any time on their mobile phones and computers.

More accurate local data

Real-time and efficient collection of local temperature and relative humidity, rain volume, wind speed, wind direction, light, pressure and other data.

Intelligently Customzied Visualization data

It can be easily set what to show on the screen with visualization data and interactive experience.

Easy to install, fast to develop

The standardized design can speed up the development and implementation process through its simplicity and ease of use.