Air quality data serves as the basis for all pollution mitigation strategies. A comprehensive air quality monitoring network provides valuable data insights to support effective air pollution management. Traditionally air quality monitoring is carried out using fixed reference-grade analyzers which are inherently very expensive. As a result, they can only be deployed in limited numbers and such sparsely located monitors fail to provide critical pollution concentration at human exposure level. As a result, air pollution exposure continues to affect human health and well-being. With technological advancements, sensor-based air monitoring devices have emerged as the latest generation of air quality monitors. Their economic cost and highly portable design make them a one-stop solution for all air quality monitoring needs. Their feasibility of dense deployment provides unprecedented details of pollutant concentration at the human exposure level. Such a monitoring network facilitates hyperlocal air quality monitoring. Hyperlocal monitoring provides robust data and high spatial resolution data. Hyperlocal monitoring helps in identifying hotspots, sources, exposure studies, community awareness, etc. Hyperlocal monitoring planning is a complex process. Several factors are to be considered for the deployment of such a dense network of monitors. The selection of device and a total number of devices has to be determined based on the scope of the monitoring, budget, and several preliminary surveys as discussed in this whitepaper. Good practice guidelines for distribution, location and a minimum number of monitoring devices are prescribed in the paper. The guidelines are suggested after a detailed review of various research papers, international case studies, and experts opinions. Calibration processes ensure better data quality. This paper describes what is hyperlocal monitoring and why it is important. The paper serves as a guide for designing and setting up an air quality monitoring network to cover an area for hyperlocal monitoring. The paper also covers the calibration methods for hyperlocal monitoring.