| Feb. 13, 2024, 4:20 p.m. |
Created
43
|
[{"model": "core.projectfund", "pk": 65738, "fields": {"project": 13970, "organisation": 11073, "amount": 296308, "start_date": "2022-02-01", "end_date": "2023-07-31", "raw_data": 180773}}]
|
|
| Jan. 30, 2024, 4:25 p.m. |
Created
43
|
[{"model": "core.projectfund", "pk": 58565, "fields": {"project": 13970, "organisation": 11073, "amount": 296308, "start_date": "2022-02-01", "end_date": "2023-07-31", "raw_data": 158157}}]
|
|
| Jan. 2, 2024, 4:15 p.m. |
Created
43
|
[{"model": "core.projectfund", "pk": 51411, "fields": {"project": 13970, "organisation": 11073, "amount": 296308, "start_date": "2022-02-01", "end_date": "2023-07-31", "raw_data": 135744}}]
|
|
| Dec. 5, 2023, 4:24 p.m. |
Created
43
|
[{"model": "core.projectfund", "pk": 44163, "fields": {"project": 13970, "organisation": 11073, "amount": 296308, "start_date": "2022-02-01", "end_date": "2023-07-30", "raw_data": 104675}}]
|
|
| Nov. 27, 2023, 2:15 p.m. |
Added
35
|
{"external_links": []}
|
|
| Nov. 21, 2023, 4:41 p.m. |
Created
43
|
[{"model": "core.projectfund", "pk": 36876, "fields": {"project": 13970, "organisation": 11073, "amount": 296308, "start_date": "2022-02-01", "end_date": "2023-07-30", "raw_data": 72299}}]
|
|
| Nov. 21, 2023, 4:41 p.m. |
Created
41
|
[{"model": "core.projectorganisation", "pk": 109249, "fields": {"project": 13970, "organisation": 17569, "role": "PARTICIPANT_ORG"}}]
|
|
| Nov. 21, 2023, 4:41 p.m. |
Created
41
|
[{"model": "core.projectorganisation", "pk": 109248, "fields": {"project": 13970, "organisation": 17569, "role": "LEAD_ORG"}}]
|
|
| Nov. 21, 2023, 4:41 p.m. |
Created
40
|
[{"model": "core.projectperson", "pk": 68544, "fields": {"project": 13970, "person": 19363, "role": "PM_PER"}}]
|
|
| Nov. 20, 2023, 2:05 p.m. |
Updated
35
|
{"title": ["", "Fruitful Forecasts"], "description": ["", "\nFruitCast Ltd, a spin out company of the University of Lincoln (UoL), are developing novel crop forecasting systems for the fresh produce sector. FruitCast are exploiting background IP that uses deep learning to detect, count and estimate weight of >3.5M strawberry fruit over a day. This provides critical starting point data for next generation crop forecasting systems. Existing forecasting tools range from simple grower intuition to models powered by machine learning to predict future yields. All existing systems are notoriously un-unreliable, typically as it is extremely difficult to measure the crop base load (e.g. number of berries on a strawberry crop, their age and weight) at the starting point of any prediction. Starting point errors create multiplicative variances in final prediction, as does uncertainty in forward weather forecasts. Hitherto no forecast system has yet closed the loop between a system that uses AI driven image analysis to measure fruit load and age (the starting point) combined with weather forecasts.\n\nHere, Fruitcast close the loop by;\n\n[1] Extending the scope of imaging IP through deep learning to calculate the age / phenological state of each detected fruit. This crucial and novel step provides unrivalled starting point data for any forecast. The data will be integrated into known biophysical models of fruit development and ensemble weather forecasts to estimate likely fruit yield, plus its uncertainty, 6 weeks ahead of any camera scan.\n\n[2] Developing an industrially robust (IP55) handheld image analysis system that can collect images, process data, count and age fruit in real time on a farm. A farm management portal will be shown on the device with visualisations of fruit count and weight.\n\nThe advantage to growers / end users is significant (>£38M to strawberry growers alone); we provide [1] a robust means to match supply and demand [2] reduce waste (640,000T fresh produce per year), [3] set price and [4] plan picking labour. FruitCast will sell the system as a service (revenue >£7M strawberries alone) initially to the soft fruit sector, then across a range of fresh produce crops. It meets the needs of an expanding fruit and vegetable sector, which policy (National Food Strategy) aims to grow by 30% over the next 8 years. Contributes to net-zero by reducing waste and supports the digital / robotic transformation of the economy articulated in the BEIS Innovation Strategy.\n\n"], "extra_text": ["", "\n\n\n\n"], "status": ["", "Closed"]}
|
|
| Nov. 20, 2023, 2:05 p.m. |
Added
35
|
{"external_links": [55271]}
|
|
| Nov. 20, 2023, 2:05 p.m. |
Created
35
|
[{"model": "core.project", "pk": 13970, "fields": {"owner": null, "is_locked": false, "coped_id": "7cd9746b-d6e4-4640-8f47-6fc4681f26fd", "title": "", "description": "", "extra_text": "", "status": "", "start": null, "end": null, "raw_data": 72282, "created": "2023-11-20T13:52:19.416Z", "modified": "2023-11-20T13:52:19.416Z", "external_links": []}}]
|
|