Personal Data* means “Information about an individual by which an individual can be identified. directly or indirectly, but not including the information of the deceased in particular.”
We will collect the following personal information:
We may receive your personal information in two ways:
The information was obtained by the following methods:
1. We store your personal information in order to provide the service. and improve our service We will ask for your consent first.
2. We collect your personal information to contact you from time to time. in presenting news change or services that are beneficial to you We will ask for your consent first.
Once personal data has been obtained from the source of personal data We will do the following with your personal data.
Such entities have adequate safeguards for personal data and will be able to enforce the rights of data subjects including statutory remedial measures that can be enforced which are detailed as follows
Retention of personal data The controller maintains your personal data as follows:
You have the right to do the following:
(1) Right to withdraw consent: You have the right to withdraw your consent. Consent to the processing of personal data that you have given us your consent to all the time Your personal data is with us.
(2) Right of access to personal data: You have the right to access personal data of You and ask us to make a copy of such personal data for you. including asking us to disclose the acquisition Personal data that you have not given us your consent to
(3) Right to rectification of personal data: You have the right to request that we Correct inaccurate information or add incomplete information.
(4) Right to erasure: You have the right to ask us to do so. may delete your information for some reason.
(5) Right to restriction of processing: You have the right to You can suspend the use of your personal information for some reason.
(6) Right to data portability: You have the right to transfer. Your personal data that you provide to us can be transferred to another data controller or yourself for some reason.
(7) The right to object to the processing of personal data (right to object): You have the right to object to the processing of personal data. can process your personal data for certain reasons.
You can contact our department staff. to process the request You can perform the above right at firstname.lastname@example.org or you can study the terms and conditions. Exceptions to the exercise of rights can be found on the website of the Ministry of Digital Economy and Society. http://www.mdes.go.th
However, you do not need to pay any fees. In carrying out the above rights which we will consider and notify the result of consideration of your request within 30 days from the date we receive the request.
During the use of the service , we will send you information about marketing activities and promoting, marketing, our products and services that we think you may be interested in for the benefit of providing services to you with full efficiency If you have agreed to receive such information from us, you have the right to withdraw such consent at any time. You can You can revoke your consent to receive information by sending an e-mail to email@example.com
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Name: ListenField Inc. and ListenField Co., Ltd.
Japan Office: Shima Building. 5F, 3-3-2 Meieki, Nakamura-ku, Nagoya, Aichi 450-0002 Japan.
Thailand Office: 3671 Mooban Ladphrao, Soi Yothin Patthana 11 Yaek 7, Praditmanutham Road, Khlongchan, Bangkapi, Bangkok 10240 Thailand
Call: +66 6101 88113
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In order to resolve a complaint regarding the Site or to receive further information regarding use of the Site, please contact us at:
ListenField Co., Ltd.
3671 Mooban Ladphrao, Soi Yothin Pattana 11 Yaek 7 Praditmanutham Rd., Khlongchan Sub-District, Bangkapi District Bangkok, THAILAND 10240
ListenField specializes in the gathering, processing, and analyzing of multilayer data to provide insightful information to agronomy professionals.ListenField aggregates environmental data, monitors crop health, and analyses phenotype and genotype to predict and suggest strategies on how to improve growth speed and quality of farmers' crops. Since our company strives for excellence in its provided services, ListenField is always exploring for flashes of inspiration to bring the industry standard to a new level. Recently, ListenField succeeded in fusing industry-standard prediction models and machine learning to enhance the accuracy of predictions by analyzing variations in specific parameters such as individual location, weather, and soil conditions.
Agro-environmental data provide relevant and accurate information to improve agricultural practices and outcomes. However, data is difficult to obtain because it is usually scattered and highly complex. ListenField provides various APIs that efficiently bring these data together and perform systematic analyses of these data, allowing our customers to seamlessly and precisely monitor the condition of their fields.
This includes for example a “soil fusion” model that assesses the soil profile deeper down to 60 centimeters anywhere. This information is available for anyone using the API. We are also utilizing up to 30 years of historical weather data and onsite sensors to accurately predict seasonal weather conditions at precise locations. Combining real-time sensor readings, with historical weather data is more effective in anticipating short-term weather trends. Lastly, the “cultivar file” that ListenField has put together can help you by telling how your plants are growing under prevailing conditions, or how your crops will turn out if they are fed differently or if climate and soil conditions change.
ListenField is developing machine vision models that empower satellite imagery analysis to help you determine the health of your crop regarding to their phenology stage. ListenField crop heath can help determine whether crops have enough fertilizers at a particular location in a plot of land, to let you add or reduce the amount of fertilizers accordingly. The technology can also tell us about “water stress”, in certain crops like orange trees.
ListenField has been developing a machine vision model that empowers satellite imagery analysis to help you determine the health of your crop depending on their phenology stage. It can help determine whether crops have enough fertilizers at a particular location in a plot of land. Fertilizers can then be added or reduced to ensure optimal “nitrogen stress” translating into more output, more stable output, and better output quality. It can also reduce the risk of “lodging” for crops such as rice and wheat -- where the stem of the plant bends over, making it very difficult to harvest the grain and greatly reducing yield.
The technology can also tell us about “water stress”, for example, in orange trees where not enough water would obviously endanger the survival of the orange tree, but just enough “water stress” will increase the sweetness of the fruit.
ListenField provides yield and growth prediction by considering the 3 important factors
The first is soil. We built what we called a “soil fusion” model that assessed the soil profile. This information is available for anyone using APIs.
The second is climate and weather conditions. For this, we used 30 years of climatological data as the benchmark. This weather pattern data is used to more accurately predict seasonal weather conditions at precise locations with the help of onsite sensors. These sensors monitor rainfall and combined with past data and can be used to anticipate short-term trends. They also monitor moisture and other factors that are important for plant growth. Our models will provide detailed and timely data on climate conditions as well as their outlook at precise locations anywhere.
The third is the cultivar coefficient. It means that plants, each with their unique genotypes, will grow and reproduce differently in response to changing environmental conditions. The “cultivar file” that ListenField has put together can help tell you how your plants are growing under prevailing conditions. Even better, it can also tell you how your crops will turn out if they are fed differently or if climate and soil conditions change.
ListenField is currently developing two predictive models for a web application. One is a model for genomic selection (GS) and another one is for genome-wide association studies (GWAS).
The models help to shorten the breeding time and thus fulfill several key goals related to the use of genetic resources and in the end the sustainability of agricultural production.
The GS model can predict the likelihood for phenotypic outcomes for specific traits (e.g. sugar content) based on (marker-based) genomic selection. It presents the data in an easy-to-understand way for user judgement.
The GWAS model assesses which gene-markers are associated with a certain variation in the phenotype (which gene-sequence is highly correlated to a phenotypic trait).