LAUSR

Sarawak is the largest state in Malaysia with 124,499 km2 land area which made up 37.5 % of Malaysia [1]. Despite having huge landmass, Sarawak’s agriculture sector is under develop. Agriculture-based food products are mostly imported from the outside, making Sarawak one of the largest food importer [2]. Sarawak is not ready to become food exporter due to low farm productivity [3]. Lack of human labour, continuous use of traditional farming methods and no effective supply chain networks are the major hurdle to the agriculture sector. Current scenario for agriculture sector is based on traditional farming, which is far from sustainable agriculture principle. Traditional farming causes environmental pollution which eventually lowering the farm productivity [2]. To improve agricultural productivity, the crop performance under different growth ecosystems such as soil conditions, soil nutrients level and environment are vital to recognised [4]. As for that reason, farmers must implement new innovative agriculture practise namely as smart agriculture or smart farm. Smart agriculture utilised Internet of Things (IoT) technology. IoT term was first coined in 1999 which describe a system where the internet is connected to the physical world via universal sensors [5]. Internet of Things (IoT) is a hot concept newly emerged that will influence how farmers manage and pursue modern farming. IoT provides automation and wireless communication between devices to devices. IoT is made possible due to the decrease of cost of technologies such as cellular network, smartphones, short range wireless communication, and sensors. IoT carry out smart function that are not able to be performed efficiently by human. Abstract: This paper presents the design and development of low-cost Internet of Things (IoT) system for remote monitoring of agriculture ecosystem. The aims of the research are to evaluate the accuracy and reliability of data collected and transmitted with developed IoT system and access from remote location. These data are then compared with the readings of the conventional stand-alone sensors or meters. The system is set in the laboratory and utilises low cost microcontroller, sensors, Wi-Fi network communication, cloud storage, mobile and web application. Microcontroller Arduino Uno ATMega328P is used with ESP8266 Wi-Fi module to enable the device to be connected to the Internet. The sensors used in this system are selected base on the plant’s growth factor. All data collected from the sensors are sent to the Cloud platform such as ThingSpeak and Blynk. Periodical monitoring is carried out on laptop and mobile phone. The results showed that the data taken from the soil moisture, soil temperature, light intensity, surrounding temperature and humidity are accurate and reliable.