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P004 Smart Palm Harvester | KLESF International Challenge 2022
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[KLESF International Challenge 2022]
Number: P004
Title of Project: Smart Palm Harvester
Name of participant #1: Khor Jin Zhe
Name of participant #2: -
Name of participant #3: -
Name of School: Honsbridge International
Project theme: Sustainable Cities and Communities (SDG 11)
Category: Primary school (12 years old or below)
Abstract of Project:
Palm oil is the largest consumed oil in the world. Malaysian oil palm industry is a multi-billions ringgit industry and is the 4th major income contributor to the country. However, the industry is also heavily depended on manual labour. In plantations, palm fresh fruit bunches need to be harvested as soon as they ripen. Failure to do so would translate to oil loss, oil of low quality and loss of revenue.
Malaysia’s oil palm sector has lost an estimated RM10.46 billion worth of unpicked palm fruits in the first five months of 2022 because of the ongoing labour shortage due to the Covid-19 pandemic. This has caused not only losses in income to the country, but also caused the price of palm oil, especially cooking oil, to escalate to record high where many people found it to be a burden. A community that could not afford the price of food is a starving community.
The Smart Palm Harvester is invented to solve the problem of labour dependency in the oil palm industry. It comprises of a driverless Harvester that could be pre-programmed to move according to the palm plantation’s map and topography, palm fresh fruit bunch ripening sensor, automated blade for harvesting the fresh fruit bunch, as well as loose fruits and bunch collector. It could ensure that ripe palm bunches could automatically be harvested on time without any loss.
The sensor at the Smart Harvester detects and identifies the palm trees and its surrounding. Once approaching the palm tree, the ripening sensor moves up to identify the color of the palm bunch. As fruits at the palm bunch do not ripen at the same time, degree of ripening at lower and upper bunch were detected to determine whether the bunch is ready to be harvested.
If the sensor detects the color of the upper and lower bunch to be green, the bunch will not be harvested as it has not ripened. The data of the bunch will be logged and recorded with estimated time (in weeks) for it to be fully ripened and ready for harvesting. With this, the Harvester could return at the estimated date to harvest the bunch.
If the bunch has not ripened, the Harvester will move on to other bunch at the tree. If the Harvester detects that both upper and lower bunch is orangey or red, it recognised that the bunch has ripened and ready for harvesting. The blade at the Harvester will then move to position itself under the frond and starts to cut the bunch. As the blade saw deeper into the bunch, its position will go upwards bit by bit in order to simulate real cutting motion.
All these are carried out in automation without human supervision or intervention.
As the bunch is being cut, some ripe fruits may detach and fall from the bunch. In conventional practice, these fruits will fall onto the ground and manual labour is needed to pick them up. However, with the Smart Harvester, these fruits will fall and collected in the Harvester, thus saving manual labour.
After the bunch is harvested and falls into the Harvester, the sensor could no longer detect the presence of the bunch. This signals the Smart Harvester that cutting has completed and the Harvester will then move on to other trees.
There are times where parts of the bunch have ripened but not all. In this case, the Harvester will not harvest the bunch as it has not fully ripened.
Recording the harvesting activity and bunch ripening state will give the data on the parts of the plantation that has been visited by the Harvester and also the estimated date that the Harvester needs to return to this part of the plantation, by which, the underripe bunches would be ready for harvesting. Besides that, it also automatically records the number of bunches that have been harvested. These data also give real time location of the Harvester for it to be traceable.
At the end of harvesting, the Harvester will automatically return to its charging station to be charged for next deployment and for the harvested bunches to be unloaded for processing.
With this, dependency on manual labour would be greatly reduced. The production of palm oil could be sustainably carried out. This would contribute to a sustainable community food system with a collaborative network that integrates sustainable food production and processing in order to enhance the environmental, economic and social health of a sustainable community. The timely oil palm harvesting will also ensure continuous and ample supply of oil with good quality for consumption and maintaining its affordable price.
#KLESFChallenge #KLESF
Number: P004
Title of Project: Smart Palm Harvester
Name of participant #1: Khor Jin Zhe
Name of participant #2: -
Name of participant #3: -
Name of School: Honsbridge International
Project theme: Sustainable Cities and Communities (SDG 11)
Category: Primary school (12 years old or below)
Abstract of Project:
Palm oil is the largest consumed oil in the world. Malaysian oil palm industry is a multi-billions ringgit industry and is the 4th major income contributor to the country. However, the industry is also heavily depended on manual labour. In plantations, palm fresh fruit bunches need to be harvested as soon as they ripen. Failure to do so would translate to oil loss, oil of low quality and loss of revenue.
Malaysia’s oil palm sector has lost an estimated RM10.46 billion worth of unpicked palm fruits in the first five months of 2022 because of the ongoing labour shortage due to the Covid-19 pandemic. This has caused not only losses in income to the country, but also caused the price of palm oil, especially cooking oil, to escalate to record high where many people found it to be a burden. A community that could not afford the price of food is a starving community.
The Smart Palm Harvester is invented to solve the problem of labour dependency in the oil palm industry. It comprises of a driverless Harvester that could be pre-programmed to move according to the palm plantation’s map and topography, palm fresh fruit bunch ripening sensor, automated blade for harvesting the fresh fruit bunch, as well as loose fruits and bunch collector. It could ensure that ripe palm bunches could automatically be harvested on time without any loss.
The sensor at the Smart Harvester detects and identifies the palm trees and its surrounding. Once approaching the palm tree, the ripening sensor moves up to identify the color of the palm bunch. As fruits at the palm bunch do not ripen at the same time, degree of ripening at lower and upper bunch were detected to determine whether the bunch is ready to be harvested.
If the sensor detects the color of the upper and lower bunch to be green, the bunch will not be harvested as it has not ripened. The data of the bunch will be logged and recorded with estimated time (in weeks) for it to be fully ripened and ready for harvesting. With this, the Harvester could return at the estimated date to harvest the bunch.
If the bunch has not ripened, the Harvester will move on to other bunch at the tree. If the Harvester detects that both upper and lower bunch is orangey or red, it recognised that the bunch has ripened and ready for harvesting. The blade at the Harvester will then move to position itself under the frond and starts to cut the bunch. As the blade saw deeper into the bunch, its position will go upwards bit by bit in order to simulate real cutting motion.
All these are carried out in automation without human supervision or intervention.
As the bunch is being cut, some ripe fruits may detach and fall from the bunch. In conventional practice, these fruits will fall onto the ground and manual labour is needed to pick them up. However, with the Smart Harvester, these fruits will fall and collected in the Harvester, thus saving manual labour.
After the bunch is harvested and falls into the Harvester, the sensor could no longer detect the presence of the bunch. This signals the Smart Harvester that cutting has completed and the Harvester will then move on to other trees.
There are times where parts of the bunch have ripened but not all. In this case, the Harvester will not harvest the bunch as it has not fully ripened.
Recording the harvesting activity and bunch ripening state will give the data on the parts of the plantation that has been visited by the Harvester and also the estimated date that the Harvester needs to return to this part of the plantation, by which, the underripe bunches would be ready for harvesting. Besides that, it also automatically records the number of bunches that have been harvested. These data also give real time location of the Harvester for it to be traceable.
At the end of harvesting, the Harvester will automatically return to its charging station to be charged for next deployment and for the harvested bunches to be unloaded for processing.
With this, dependency on manual labour would be greatly reduced. The production of palm oil could be sustainably carried out. This would contribute to a sustainable community food system with a collaborative network that integrates sustainable food production and processing in order to enhance the environmental, economic and social health of a sustainable community. The timely oil palm harvesting will also ensure continuous and ample supply of oil with good quality for consumption and maintaining its affordable price.
#KLESFChallenge #KLESF
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