Abstract: Tricholoma matsutake (T. matsutake) is a special type of fungus known as “the king of bacteria”, and has a very high economic value. However, it is also very difficult to transport due to its corruptibility. Therefore, tracing and tracking the quality and safety of T. matsutake in the cold chain is very important and necessary. Based on changes in the cold chain, environmental parameters determine the safety of T. matsutake is a viable option. This paper developed and tested a real-time monitoring traceability system (RM-TM) using emerging Internet of Things (IoT) technologies for monitoring the cold chain logistics environmental parameters of T. matsutake. Finally, system testing and evaluation have shown that RM-TM can track and monitor temperature, humidity, oxygen and carbon dioxide fluctuations in the cold chain in real-time. In addition, the collected data can be used to increase the transparency of cold chain logistics and to more effectively control quality, safety, and traceability. In general, the system evaluation results show that it is reliable and meets the requirements of users.
In the Energy Management system, the main constraints are accurate data, energy monitoring and implementation of visual data for consumers. This Project is intended in designing a system at home or industry which monitors the temperature consumption of cold storage, which is designed to calculate the total energy consumption. A server will be created with appropriate channels to monitor the energy consumption from each of the devices respectively. These data will be uploaded to the server at the monitoring end. Considering all this data, an individual energy load profile for each of the devices is displayed on the web-page.
Keywords: Transmitter, Receiver, Antenna, Fading, Peak to average power ratio (PAPR), Bit error rate (BER), Symbol error rate (SER), Frame error rate (FER), Inter carrier interference (ICI), Inter symbol interference (ISI), Cyclic prefix (CP), Maximal ratio combining (MRC), Maximum sum rate and Minimum error rate etc.
Cite:
Ambika Nanwatkar, Sahil Jawade, Sagar Hivarale, Vijay Gaikwad, Lalita Patle, Sneha Parbat, Nikita Paul, Prof. Diksha Khare, “IOT BASED FOOD COLD STORAGE MONITORING AND CONTROLLING SYSTEM”, IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 13, no. 2, 2024, Crossref https://doi.org/10.17148/IJARCCE.2024.13316.
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DOI:
10.17148/IJARCCE.2024.13316
